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Run 41a17b33

[manual-retry-of:793f0eef-6e83-4359-a0c0-94469d5cfcae] The previous Claude Code run ended without completing. Pick up where it left off — do not redo work that already finished cleanly.

Original request
[auto-recovery-for:64a794c8-1dc0-44f4-9491-3563c3773c1e]

The previous Claude Code run failed or crashed.

First diagnose why it stopped using the transcript below. Then fix or work around the problem if possible and continue the original request to a final useful result. Do not repeat completed work. If the root cause is external credentials, unavailable infrastructure, missing human approval, or another issue you cannot safely fix, stop with a concise blocker that includes the evidence and the exact next manual action.
Original request
experiment-orchestrator-for:3ccf4de3-57e2-4e55-a32c-9a58399093cf

Drive experiment 077ae4c7-e816-4dd8-a150-ad8fe19cb795 from approved plan through awaiting_promotion. Sub-agents are loaded from .claude/agents/.
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Runner stopped during active session (SIGTERM); queued automatic recovery.
Previous run transcript
- 2026-05-13T13:10:43.660Z started: kind=apply
- 2026-05-13T13:11:00.990Z failed: Runner stopped during active session (SIGTERM); queued automatic recovery.

Previous failure reason:
Runner stopped during active session (SIGTERM); queued automatic recovery.
Statuscompleted168 events · latest 1349h 6m ago

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This run resumes 64a794c8.

Plan

Goal

Run one balanced 2^5 factorial across five contested factors that prior single-axis experiments could not disentangle, stratified over three source personas (librarian, surgeon, programmer), and rank which factors actually move `[ZLT]` source-rate and off-diagonal leakage under LoRA SFT on Qwen2.5-7B-Instruct. Replaces ad-hoc one-axis sweeps with a single interpretable screen that absorbs the open scope of #361 / #339 / #353 and the still-unrun grid in #46.

Hypothesis

Conditional on the design in the experiment body (96 cells = 3 sources × 32 cells, with seeds 137+256 on the top-3 cells per source), the five factors split into three classes: 1. **Load-bearing (large main effects):** Factor **A** (system-prompt length, short→long) and Factor **E** (loss mask, marker-only→whole-completion) dominate source-rate. A1 raises source-rate; E1 lowers it. Factor **D** (off-policy data) lowers source-rate vs on-policy at matched length. 2. **Non-monotonic / collapsing:** Factor **B** (answer-format length, short→long) collapses source-rate at the long extreme even when system-prompt length is short, replicating #295's null at the long tail. 3. **Near-zero net effect:** Factor **C** (persona vs lexically matched non-persona framing) has near-zero independent main effect on source-rate once A is controlled, but a measurable interaction with A (A×C) carrying most of #337's "persona" signal. For off-diagonal leakage, A1 and E1 both reduce leakage; D1 has the opposite sign to its effect on source-rate.

Prediction

At α=0.05 with question-clustered bootstrap for source-rate and persona-clustered for leakage (per `--bootstrap-cluster-sr question --bootstrap-cluster-lr persona`): - |d(A on SR)| ≥ 0.4 averaged across the three source slabs, sign positive. - |d(E on SR)| ≥ 0.3, sign positive for E0 (marker-only) over E1 (whole-completion). - |d(D on SR)| ≥ 0.2, sign positive for D0 (on-policy) over D1 (off-policy). - |d(B on SR)| ≥ 0.3 at the B1 extreme with a non-monotone shape vs B0. - |d(C on SR)| < 0.15 once A is partialled out. - Pre-registered F1×F2 interaction: A×B yields a measurable interaction term (>2× the next-largest interaction) because the question-prefix tokens for B compete with persona-conditioning context from A. Signs and magnitudes are read off pod 3's `main_effects.json` / `interactions.json` after Phase 4 aggregation.

Kill Criterion

Pull the plug — and treat the screen as uninterpretable — if any of the following fires: 1. **Phase 0 pre-screen fails:** base-model contamination on the 24×20×5 eval panel exceeds the pre-registered threshold (`kill_criterion_4_passed=False` in pod 0). Pod 0 raises `SystemExit` and the run aborts. 2. **Phase 1 smoke fails:** the 8-cell resolution-III fractional factorial on librarian returns verdict ≠ `pass` (e.g. uniform near-zero or saturated source-rates across all 8 cells). Indicates the training recipe or marker setup is broken at the level of the librarian source, so the full 32-cell sweep cannot rank factors. 3. **Sign instability across sources:** after Phase 4 aggregation, ≥3 of the 5 main effects flip sign across the three sources. The 5-factor framing is wrong and we re-scope at the persona-class level before any further dispatch. 4. **All main effects below noise:** all 5 main effects have |Cohen's d| < 0.15 for source-rate AND for leakage across all three sources. The screen has no statistical power at this dataset size; we revisit pos/neg counts or LoRA rank before re-running. 5. **Cost overrun:** any single pod exceeds 24 h wall-time (the `phase4-max-wait-seconds` hard cap), or aggregate spend exceeds ~$160 (≈ 1.5× the planned compute estimate below). Operator stops the run and triages. 6. **Recovery-specific bootstrap silence:** if all four pods reach `RUNNING` but emit zero `5% · bootstrap complete` progress notes within 5 min of `RUNNING`, the operator stops the dispatch (suspected bootstrap-wrapper hang or account-credential flake — see Risks §Recovery context). This is the explicit detector for the failure mode that triggered this auto-recovery.

Experimental Setup

Faithful to the body's design and the persisted `pod_spec` on `experiments.077ae4c7-…`, instantiated by the existing `eps.experiments.marker_factor_screen` entry point. - **Branch / commit:** `experiment-365` @ `b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7` (matches the patched `pod_spec` and the `_factor_screen/` module tree currently on disk under `/home/thomasjiralerspong/explore-persona-space/eps/experiments/`). The runner injects `SAGAN_EPS_BRANCH=experiment-365` and `SAGAN_EPS_COMMIT_SHA=b1a24b4b...` so the bootstrap wrapper checks out the exact commit on each pod. - **Model and tooling:** Qwen2.5-7B-Instruct, LoRA r=32 α=64, lr=1e-5, 3 epochs. 200 positives + 400 negatives per source. 24-persona × 20-question × 5-completion eval panel with `eval_max_new_tokens=2048`. Clustered bootstrap, question-clustered for source-rate, persona-clustered for leakage. - **Pod topology (4 pods, role-distinct):** - **Pod 0** (`librarian`): Phase 0 base-model contamination pre-screen → Phase 1 res-III smoke → Phase 2 full 32-cell librarian slab at seed 42 → Phase 3 multi-seed top-3 librarian cells (seeds 137, 256). Runs `--run-pre-screen --run-smoke`. - **Pod 1** (`surgeon`): Phase 2 32-cell surgeon slab at seed 42 → Phase 3 multi-seed top-3 surgeon cells. No pre-screen/smoke flags (those gate the whole experiment from pod 0). - **Pod 2** (`programmer`): same shape as pod 1 for the programmer slab. - **Pod 3** (`aggregator-and-overflow`): waits up to 24 h for the three slab `metrics.json` files, then builds `main_effects.json`, `interactions.json`, the persona × cell heatmap, and the clean-result HTML. Runs `--role aggregator-and-overflow --build-figures --write-clean-result --label-f1xf2-preregistered`. - **Pre-registration:** the A×B (system-prompt length × answer-format length) interaction is the one pre-registered two-way; the other nine are reported but labeled exploratory in the aggregator output.

Compute and Hardware

**Topology.** Four pods, each 1× A100 80GB. This is a deliberate, multi-pod array under clause (c) — explicit per-pod role isolation — not the discouraged "one-pod-per-source" anti-pattern: - Pods 0/1/2 are the three source slabs and could in principle batch-share one node, but the script's `--pod-index` / `--source-persona` / `--num-pods` contract (`marker_factor_screen.py:69-79, 153-265`) and pod 0's extra Phase 0/1 gates make them heterogeneous workloads with independent kill criteria. - Pod 3 is a long-running stateful aggregator that polls sibling pods' `metrics.json` until they exist; it must outlive any single training process and runs different code (figure-building, no SFT). It would be wasteful to keep a 4-GPU node alive for the ~24 h aggregator wait. Consolidating to a single 4-GPU node would require an `accelerate`-style rewrite of the entry point that does not exist on `experiment-365`. That rewrite is out of scope for this recovery dispatch and is the right shape for a future ablation. **Time and cost.** - Compute: 4 pods × 1 GPU × 18 h × **$1.49/GPU-hr** (A100 80GB SXM, RunPod Secure Cloud, May 2026 reference rate per the system-prompt rate table) ≈ **$107**. - Storage: 4 × (100 GB volume + 100 GB container disk) × 18 h at $0.10/GB-month ≈ **$2**. - **Total estimated spend ≈ $110** (rounded to two significant figures), with a $160 cost-overrun kill at 1.5×. Rates may drift; the auditor's input is the rate stated here. **Substitution policy delta vs prior dispatch.** The persisted `pod_spec.substitution_policy.account.prefer` was `"team"`. For this recovery dispatch, `prefer` is flipped to `"personal"` because both prior team-account dispatches (`15038ff7…` and the `910a65d6…` whose failure triggered this recovery) hit `Pod not found in account=team` at ~10–15 min after reaching `RUNNING`. The personal account remains in `allowed` so future revisions can swap back once the team-account flake is resolved. The script binds one GPU per pod, so `gpuCount` stays pinned to 1. A100/H100/H200 ≥80 GB are all acceptable; Secure preferred over Community.

Artifacts

- **Per-source pod (0/1/2) under `/workspace/runs/365/pod<i>/<source>/`:** `metrics.json`, LoRA adapters under `adapters/`, `figures/` (per-source heatmap, A×B interaction plot, factor-ranking bar chart). - **Pod 0 extras under `/workspace/runs/365/pod0/`:** `pre_screen.json`, `smoke.json`. - **Pod 3 aggregator under `/workspace/runs/365/pod3/`:** `main_effects.json`, `interactions.json`, `aggregate_metrics.json`, `figures/persona_cell_heatmap.svg`, `figures/factor_ranking.svg`, `figures/AxB_interaction.svg`, `clean_result.html` (the experiment-page `body`). - **Sagan-side:** new `experiments.body` HTML written by `--write-clean-result` and the aggregator figures uploaded as `html_artifact` / `image` figures linked to experiment #365.

Verification

Pre-flight (operator does this before re-dispatch and at first progress-tick): 1. **Spec parity check.** Diff this plan's `runpod-spec` against the persisted `experiments.077ae4c7…pod_spec`: identical except for `substitution_policy.account.prefer` (`"team"` → `"personal"`). No other field changes. 2. **Bootstrap progress check.** Within 5 min of each pod reaching `RUNNING`, the runner expects a `5% · bootstrap complete` progress event from each of the four pods. If zero pods emit it (the recovery-trigger failure mode), abort and SSH into one pod to tail `journalctl` and the bootstrap wrapper log before retrying. 3. **Phase 0/1 gates.** Pod 0 must emit `kill_pre_screen` verdict=`passed` and `kill_smoke` verdict=`pass` before pods 1/2/3 are allowed to consume significant compute. The script raises `SystemExit` on failure; the runner surfaces that as a hard stop. Post-run (operator checks before declaring the screen interpretable): 4. `main_effects.json` reports five main effects with bootstrap CIs and Cohen's d for both source-rate and leakage. All three sources represented in the underlying slab summaries. 5. `interactions.json` reports all ten two-way interactions with the A×B row carrying a `pre_registered: true` flag. 6. `clean_result.html` follows `docs/clean-result-guidelines.md` (TL;DR → primary plot → Experimental design dropdown) and is attached to `experiments.body` on experiment #365.

Risks and Red Team

**Risk 1 — multi-pod partial-dispatch sensitivity.** Per the system prompt, partial dispatch of a multi-pod array is treated as a hard failure; this is what happened at 08:56 (2/4 came up). The substitution policy below allows the provisioner to fall back to community cloud or back to the team account; if capacity is still tight, the operator should consider running pod 0 alone as a 1-pod smoke before fanning out. **Risk 2 — recurring team-account vanishing (the recovery trigger).** Two prior team-account dispatches (`15038ff7…` and `910a65d6…`) hit `Pod not found in account=team` 10–15 min after all four pods reported `RUNNING`. Root cause is still ambiguous (team-account credentials event vs. bootstrap-wrapper hang vs. RunPod team-account inventory drift). This recovery dispatch flips `account.prefer` to `personal` so we exercise a different surface. If the same vanishing fires under `personal`, the failure is upstream of the account choice and the operator should SSH into one pod to tail `journalctl` / wrapper logs before any further retry, per the prior planner's recommendation. Verification step 2 is the explicit detector. **Risk 3 — single-seed factor ranks.** Most cells run at seed 42 only; multi-seed coverage is restricted to the top-3 per source. A factor ranked 2nd or 3rd whose true effect is borderline could swap with a 4th-ranked factor under seed noise. We accept this risk because broadening multi-seed to all 32×3 cells multiplies compute by 3× and is out of cost scope. **Risk 4 — F1×F2 pre-registration vs the other 9 interactions.** With 10 two-way interactions reported and a single one pre-registered, multiple-comparison hygiene matters. The aggregator labels exploratory interactions accordingly; we do not claim significance for any exploratory interaction without a confirmatory experiment. **Risk 5 — A/B confound on user-message tokens.** Even though B is induced by a natural format instruction, the instruction tokens still live inside the user message and could shift attention patterns independent of completion length. This is a genuine confound the screen cannot fully separate; the A×B interaction term is the diagnostic and is pre-registered for that reason. **Critique loop notes.** This is a re-finalization of an owner-approved design (the planJson is fully populated and the design body has been stable across multiple rounds). The scientific design is unchanged from the prior approved plan; the only delta is `runpod-spec.substitution_policy.account.prefer` flipping from `"team"` to `"personal"` plus the corresponding addition of kill criterion #6 (bootstrap-silence detector) and Verification step 2. I ran the consistency check internally rather than the full paired-critic loop because (a) the design is owner-approved, (b) the open question is purely whether the `runpod-spec` matches the patched DB state and the script's CLI contract, and (c) the script's `parse_args` (`marker_factor_screen.py:62-138`) was re-verified against each pod's `dockerArgs`. Loops run: 0 (re-finalize); merged verdict: pass for methodology, statistics, and alternative-explanations because no design field changed; no follow-ups intentionally dropped. If a future revision changes any scientific field, that revision should re-enter the full paired-critic loop.

Likely Clean Result

A `body` HTML on experiment #365 following `docs/clean-result-guidelines.md`: - **TL;DR (single paragraph in first person):** "I ran a balanced 2^5 factorial across five marker-implantation factors on three source personas. System-prompt length and loss-mask scope were the two load-bearing knobs, both with Cohen's d > 0.4 on source-rate; persona framing had near-zero independent effect once length was controlled, confirming #340. Long answer-format prompts collapsed source-rate at the extreme, replicating #295. Off-policy data lost ~0.2 d of source-rate vs on-policy at matched length." - **Primary plot:** a single bar chart of the five main-effect Cohen's d's on source-rate with 95% bootstrap CIs, ordered largest-to-smallest, with plain-English axis labels ("system-prompt length", "loss masks marker only", etc.) and SVG `<title>` hover tooltips carrying the underlying mean and CI. - **Experimental design dropdown:** the 32-cell factor table, the 3-source stratification, the seed plan, the bootstrap scheme, and the kill-criterion list — collapsed by default. Sections deliberately omitted per the clean-result guidelines: separate Background / Methodology h2s, standing caveats, references to the abandoned single-axis sweeps, and the additional per-source heatmaps (those live as linked figures, not in the body).

Approval Checklist

- [x] **Goal** matches the experiment record title and absorbs the open scope of #361 / #339 / #353 / #46. - [x] **Hypothesis** is specific: five factors split into three classes with signed predictions for each. - [x] **Prediction** is falsifiable: numeric Cohen's d thresholds with α=0.05 and a named bootstrap scheme. - [x] **Kill criterion** has six concrete triggers, including the new bootstrap-silence detector that directly responds to the recovery-trigger failure mode. - [x] **Compute and Hardware** estimates 4 × 1 × 18 h × $1.49 ≈ $107 compute + ~$2 storage = **~$110 total** at A100 80GB SXM Secure Cloud rates; cost-overrun kill at $160. Multi-pod array is justified under clause (c) per-pod role isolation; consolidation deferred to a future ablation. - [x] **Artifacts** enumerated per-pod and aggregator with `/workspace/runs/365/...` paths matching the script's directory contract. - [x] **Verification** covers spec parity, the bootstrap-progress detector, Phase 0/1 kill gates, and the aggregator's required JSONs / clean-result HTML. - [x] **Risks** explicitly cover the team-account vanishing failure that triggered this recovery and document the rationale for flipping `account.prefer` to `personal`. - [x] **Likely clean result** follows `docs/clean-result-guidelines.md` (TL;DR → primary plot → design dropdown, first-person voice, no standing caveats). - [x] **`runpod-spec` matches the plan**: 4 pods, A100 80GB Secure Cloud preferred, single-GPU per pod, `account.prefer=personal` with `team` retained in `allowed`, and per-pod `dockerArgs` identical to the persisted `experiments.077ae4c7…pod_spec` save for that one substitution-policy field. ```runpod-spec [ { "name": "marker-screen-365-pod0-pre-and-source-librarian", "gpuType": "A100", "gpuCount": 1, "volumeGb": 100, "containerDiskGb": 100, "cloudType": "SECURE", "estimatedMinutes": 1080, "env": { "SAGAN_EPS_BRANCH": "experiment-365", "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7" }, "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 0 --num-pods 4 --source-persona librarian --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --run-pre-screen --run-smoke --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'", "config": { "command": "Pod 0: Phase 0 base-model contamination pre-screen on 24x20x5 eval panel + Phase 1 8-cell res-III librarian smoke (kill gates only) + Phase 2 32-cell librarian slab at primary seed + Phase 3 multi-seed top-3 librarian cells (seeds 137, 256). Clustered bootstrap (question-clustered SR, persona-clustered LR).", "artifacts": [ "/workspace/runs/365/pod0/pre_screen.json", "/workspace/runs/365/pod0/smoke.json", "/workspace/runs/365/pod0/librarian/metrics.json", "/workspace/runs/365/pod0/librarian/adapters/", "/workspace/runs/365/pod0/figures/" ] }, "substitution_policy": { "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 }, "gpuCount": { "min": 1, "max": 1 }, "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" }, "dataCenterId": { "allowed": "any" }, "account": { "allowed": ["personal", "team"], "prefer": "personal" }, "volumeGb": { "min": 100 }, "containerDiskGb": { "min": 100 } }, "consolidation": { "may_merge_pods": false, "merge_target_max_gpus_per_pod": 1 } }, { "name": "marker-screen-365-pod1-source-surgeon", "gpuType": "A100", "gpuCount": 1, "volumeGb": 100, "containerDiskGb": 100, "cloudType": "SECURE", "estimatedMinutes": 1080, "env": { "SAGAN_EPS_BRANCH": "experiment-365", "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7" }, "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 1 --num-pods 4 --source-persona surgeon --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'", "config": { "command": "Pod 1: Phase 2 32-cell surgeon slab at primary seed 42 + Phase 3 multi-seed top-3 surgeon cells (seeds 137, 256). Clustered bootstrap (question-clustered SR, persona-clustered LR).", "artifacts": [ "/workspace/runs/365/pod1/surgeon/metrics.json", "/workspace/runs/365/pod1/surgeon/adapters/", "/workspace/runs/365/pod1/figures/" ] }, "substitution_policy": { "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 }, "gpuCount": { "min": 1, "max": 1 }, "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" }, "dataCenterId": { "allowed": "any" }, "account": { "allowed": ["personal", "team"], "prefer": "personal" }, "volumeGb": { "min": 100 }, "containerDiskGb": { "min": 100 } }, "consolidation": { "may_merge_pods": false, "merge_target_max_gpus_per_pod": 1 } }, { "name": "marker-screen-365-pod2-source-programmer", "gpuType": "A100", "gpuCount": 1, "volumeGb": 100, "containerDiskGb": 100, "cloudType": "SECURE", "estimatedMinutes": 1080, "env": { "SAGAN_EPS_BRANCH": "experiment-365", "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7" }, "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 2 --num-pods 4 --source-persona programmer --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'", "config": { "command": "Pod 2: Phase 2 32-cell programmer slab at primary seed 42 + Phase 3 multi-seed top-3 programmer cells (seeds 137, 256). Clustered bootstrap (question-clustered SR, persona-clustered LR).", "artifacts": [ "/workspace/runs/365/pod2/programmer/metrics.json", "/workspace/runs/365/pod2/programmer/adapters/", "/workspace/runs/365/pod2/figures/" ] }, "substitution_policy": { "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 }, "gpuCount": { "min": 1, "max": 1 }, "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" }, "dataCenterId": { "allowed": "any" }, "account": { "allowed": ["personal", "team"], "prefer": "personal" }, "volumeGb": { "min": 100 }, "containerDiskGb": { "min": 100 } }, "consolidation": { "may_merge_pods": false, "merge_target_max_gpus_per_pod": 1 } }, { "name": "marker-screen-365-pod3-aggregator-and-overflow", "gpuType": "A100", "gpuCount": 1, "volumeGb": 100, "containerDiskGb": 100, "cloudType": "SECURE", "estimatedMinutes": 1080, "env": { "SAGAN_EPS_BRANCH": "experiment-365", "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7" }, "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 3 --num-pods 4 --role aggregator-and-overflow --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --build-figures --write-clean-result --label-f1xf2-preregistered --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'", "config": { "command": "Pod 3: Phase 4 aggregator. Waits up to 24h for pods 0/1/2 metrics.json files, then builds main_effects.json, interactions.json (with A x B pre-registered), the persona x cell heatmap, the factor-ranking bar chart, the A x B interaction plot, and the clean-result HTML attached to experiments.body.", "artifacts": [ "/workspace/runs/365/pod3/main_effects.json", "/workspace/runs/365/pod3/interactions.json", "/workspace/runs/365/pod3/aggregate_metrics.json", "/workspace/runs/365/pod3/figures/persona_cell_heatmap.svg", "/workspace/runs/365/pod3/figures/factor_ranking.svg", "/workspace/runs/365/pod3/figures/AxB_interaction.svg", "/workspace/runs/365/pod3/clean_result.html" ] }, "substitution_policy": { "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 }, "gpuCount": { "min": 1, "max": 1 }, "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" }, "dataCenterId": { "allowed": "any" }, "account": { "allowed": ["personal", "team"], "prefer": "personal" }, "volumeGb": { "min": 100 }, "containerDiskGb": { "min": 100 } }, "consolidation": { "may_merge_pods": false, "merge_target_max_gpus_per_pod": 1 } } ] ``` **Recovery summary.** Diagnosed the failure as the recurring team-account post-RUNNING vanishing (Risk 2 from the prior plan). Re-emitted the owner-approved 4-pod plan unchanged except for: (1) `substitution_policy.account.prefer` flipped from `team` to `personal`; (2) kill criterion #6 added as an explicit detector for the same failure mode under the new account; (3) Verification step 2 documents the 5-min bootstrap-progress check. The persisted `experiments.077ae4c7…pod_spec` already has `personal` in `account.allowed`, so this is a scope-preserving recovery, not a design change.

I have enough context. The previous direct-dispatch failed because all 4 RunPod pods successfully reached RUNNING on the team account, then simultaneously disappeared from inventory ~11 min later — the exact recurring failure mode the prior planner flagged as Risk 2. The persisted substitution_policy already allows personal as a fallback, but prefer="team" keeps re-dispatching into the failing surface. The minimal scope-preserving fix is to flip account.prefer to personal for this recovery dispatch and re-emit the otherwise unchanged owner-approved plan.

Goal

Run one balanced 2^5 factorial across five contested factors that prior single-axis experiments could not disentangle, stratified over three source personas (librarian, surgeon, programmer), and rank which factors actually move [ZLT] source-rate and off-diagonal leakage under LoRA SFT on Qwen2.5-7B-Instruct. Replaces ad-hoc one-axis sweeps with a single interpretable screen that absorbs the open scope of #361 / #339 / #353 and the still-unrun grid in #46.

Hypothesis

Conditional on the design in the experiment body (96 cells = 3 sources × 32 cells, with seeds 137+256 on the top-3 cells per source), the five factors split into three classes:

  1. Load-bearing (large main effects): Factor A (system-prompt length, short→long) and Factor E (loss mask, marker-only→whole-completion) dominate source-rate. A1 raises source-rate; E1 lowers it. Factor D (off-policy data) lowers source-rate vs on-policy at matched length.
  2. Non-monotonic / collapsing: Factor B (answer-format length, short→long) collapses source-rate at the long extreme even when system-prompt length is short, replicating #295's null at the long tail.
  3. Near-zero net effect: Factor C (persona vs lexically matched non-persona framing) has near-zero independent main effect on source-rate once A is controlled, but a measurable interaction with A (A×C) carrying most of #337's "persona" signal.

For off-diagonal leakage, A1 and E1 both reduce leakage; D1 has the opposite sign to its effect on source-rate.

Prediction

At α=0.05 with question-clustered bootstrap for source-rate and persona-clustered for leakage (per --bootstrap-cluster-sr question --bootstrap-cluster-lr persona):

  • |d(A on SR)| ≥ 0.4 averaged across the three source slabs, sign positive.
  • |d(E on SR)| ≥ 0.3, sign positive for E0 (marker-only) over E1 (whole-completion).
  • |d(D on SR)| ≥ 0.2, sign positive for D0 (on-policy) over D1 (off-policy).
  • |d(B on SR)| ≥ 0.3 at the B1 extreme with a non-monotone shape vs B0.
  • |d(C on SR)| < 0.15 once A is partialled out.
  • Pre-registered F1×F2 interaction: A×B yields a measurable interaction term (>2× the next-largest interaction) because the question-prefix tokens for B compete with persona-conditioning context from A.

Signs and magnitudes are read off pod 3's main_effects.json / interactions.json after Phase 4 aggregation.

Kill Criterion

Pull the plug — and treat the screen as uninterpretable — if any of the following fires:

  1. Phase 0 pre-screen fails: base-model contamination on the 24×20×5 eval panel exceeds the pre-registered threshold (kill_criterion_4_passed=False in pod 0). Pod 0 raises SystemExit and the run aborts.
  2. Phase 1 smoke fails: the 8-cell resolution-III fractional factorial on librarian returns verdict ≠ pass (e.g. uniform near-zero or saturated source-rates across all 8 cells). Indicates the training recipe or marker setup is broken at the level of the librarian source, so the full 32-cell sweep cannot rank factors.
  3. Sign instability across sources: after Phase 4 aggregation, ≥3 of the 5 main effects flip sign across the three sources. The 5-factor framing is wrong and we re-scope at the persona-class level before any further dispatch.
  4. All main effects below noise: all 5 main effects have |Cohen's d| < 0.15 for source-rate AND for leakage across all three sources. The screen has no statistical power at this dataset size; we revisit pos/neg counts or LoRA rank before re-running.
  5. Cost overrun: any single pod exceeds 24 h wall-time (the phase4-max-wait-seconds hard cap), or aggregate spend exceeds ~$160 (≈ 1.5× the planned compute estimate below). Operator stops the run and triages.
  6. Recovery-specific bootstrap silence: if all four pods reach RUNNING but emit zero 5% · bootstrap complete progress notes within 5 min of RUNNING, the operator stops the dispatch (suspected bootstrap-wrapper hang or account-credential flake — see Risks §Recovery context). This is the explicit detector for the failure mode that triggered this auto-recovery.

Experimental Setup

Faithful to the body's design and the persisted pod_spec on experiments.077ae4c7-…, instantiated by the existing eps.experiments.marker_factor_screen entry point.

  • Branch / commit: experiment-365 @ b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7 (matches the patched pod_spec and the _factor_screen/ module tree currently on disk under /home/thomasjiralerspong/explore-persona-space/eps/experiments/). The runner injects SAGAN_EPS_BRANCH=experiment-365 and SAGAN_EPS_COMMIT_SHA=b1a24b4b... so the bootstrap wrapper checks out the exact commit on each pod.
  • Model and tooling: Qwen2.5-7B-Instruct, LoRA r=32 α=64, lr=1e-5, 3 epochs. 200 positives + 400 negatives per source. 24-persona × 20-question × 5-completion eval panel with eval_max_new_tokens=2048. Clustered bootstrap, question-clustered for source-rate, persona-clustered for leakage.
  • Pod topology (4 pods, role-distinct):
    • Pod 0 (librarian): Phase 0 base-model contamination pre-screen → Phase 1 res-III smoke → Phase 2 full 32-cell librarian slab at seed 42 → Phase 3 multi-seed top-3 librarian cells (seeds 137, 256). Runs --run-pre-screen --run-smoke.
    • Pod 1 (surgeon): Phase 2 32-cell surgeon slab at seed 42 → Phase 3 multi-seed top-3 surgeon cells. No pre-screen/smoke flags (those gate the whole experiment from pod 0).
    • Pod 2 (programmer): same shape as pod 1 for the programmer slab.
    • Pod 3 (aggregator-and-overflow): waits up to 24 h for the three slab metrics.json files, then builds main_effects.json, interactions.json, the persona × cell heatmap, and the clean-result HTML. Runs --role aggregator-and-overflow --build-figures --write-clean-result --label-f1xf2-preregistered.
  • Pre-registration: the A×B (system-prompt length × answer-format length) interaction is the one pre-registered two-way; the other nine are reported but labeled exploratory in the aggregator output.

Compute and Hardware

Topology. Four pods, each 1× A100 80GB. This is a deliberate, multi-pod array under clause (c) — explicit per-pod role isolation — not the discouraged "one-pod-per-source" anti-pattern:

  • Pods 0/1/2 are the three source slabs and could in principle batch-share one node, but the script's --pod-index / --source-persona / --num-pods contract (marker_factor_screen.py:69-79, 153-265) and pod 0's extra Phase 0/1 gates make them heterogeneous workloads with independent kill criteria.
  • Pod 3 is a long-running stateful aggregator that polls sibling pods' metrics.json until they exist; it must outlive any single training process and runs different code (figure-building, no SFT). It would be wasteful to keep a 4-GPU node alive for the ~24 h aggregator wait.

Consolidating to a single 4-GPU node would require an accelerate-style rewrite of the entry point that does not exist on experiment-365. That rewrite is out of scope for this recovery dispatch and is the right shape for a future ablation.

Time and cost.

  • Compute: 4 pods × 1 GPU × 18 h × $1.49/GPU-hr (A100 80GB SXM, RunPod Secure Cloud, May 2026 reference rate per the system-prompt rate table) ≈ $107.
  • Storage: 4 × (100 GB volume + 100 GB container disk) × 18 h at $0.10/GB-month ≈ $2.
  • Total estimated spend ≈ $110 (rounded to two significant figures), with a $160 cost-overrun kill at 1.5×.

Rates may drift; the auditor's input is the rate stated here.

Substitution policy delta vs prior dispatch. The persisted pod_spec.substitution_policy.account.prefer was "team". For this recovery dispatch, prefer is flipped to "personal" because both prior team-account dispatches (15038ff7… and the 910a65d6… whose failure triggered this recovery) hit Pod not found in account=team at ~10–15 min after reaching RUNNING. The personal account remains in allowed so future revisions can swap back once the team-account flake is resolved. The script binds one GPU per pod, so gpuCount stays pinned to 1. A100/H100/H200 ≥80 GB are all acceptable; Secure preferred over Community.

Artifacts

  • Per-source pod (0/1/2) under /workspace/runs/365/pod<i>/<source>/: metrics.json, LoRA adapters under adapters/, figures/ (per-source heatmap, A×B interaction plot, factor-ranking bar chart).
  • Pod 0 extras under /workspace/runs/365/pod0/: pre_screen.json, smoke.json.
  • Pod 3 aggregator under /workspace/runs/365/pod3/: main_effects.json, interactions.json, aggregate_metrics.json, figures/persona_cell_heatmap.svg, figures/factor_ranking.svg, figures/AxB_interaction.svg, clean_result.html (the experiment-page body).
  • Sagan-side: new experiments.body HTML written by --write-clean-result and the aggregator figures uploaded as html_artifact / image figures linked to experiment #365.

Verification

Pre-flight (operator does this before re-dispatch and at first progress-tick):

  1. Spec parity check. Diff this plan's runpod-spec against the persisted experiments.077ae4c7…pod_spec: identical except for substitution_policy.account.prefer ("team""personal"). No other field changes.
  2. Bootstrap progress check. Within 5 min of each pod reaching RUNNING, the runner expects a 5% · bootstrap complete progress event from each of the four pods. If zero pods emit it (the recovery-trigger failure mode), abort and SSH into one pod to tail journalctl and the bootstrap wrapper log before retrying.
  3. Phase 0/1 gates. Pod 0 must emit kill_pre_screen verdict=passed and kill_smoke verdict=pass before pods 1/2/3 are allowed to consume significant compute. The script raises SystemExit on failure; the runner surfaces that as a hard stop.

Post-run (operator checks before declaring the screen interpretable):

  1. main_effects.json reports five main effects with bootstrap CIs and Cohen's d for both source-rate and leakage. All three sources represented in the underlying slab summaries.
  2. interactions.json reports all ten two-way interactions with the A×B row carrying a pre_registered: true flag.
  3. clean_result.html follows docs/clean-result-guidelines.md (TL;DR → primary plot → Experimental design dropdown) and is attached to experiments.body on experiment #365.

Risks and Red Team

Risk 1 — multi-pod partial-dispatch sensitivity. Per the system prompt, partial dispatch of a multi-pod array is treated as a hard failure; this is what happened at 08:56 (2/4 came up). The substitution policy below allows the provisioner to fall back to community cloud or back to the team account; if capacity is still tight, the operator should consider running pod 0 alone as a 1-pod smoke before fanning out.

Risk 2 — recurring team-account vanishing (the recovery trigger). Two prior team-account dispatches (15038ff7… and 910a65d6…) hit Pod not found in account=team 10–15 min after all four pods reported RUNNING. Root cause is still ambiguous (team-account credentials event vs. bootstrap-wrapper hang vs. RunPod team-account inventory drift). This recovery dispatch flips account.prefer to personal so we exercise a different surface. If the same vanishing fires under personal, the failure is upstream of the account choice and the operator should SSH into one pod to tail journalctl / wrapper logs before any further retry, per the prior planner's recommendation. Verification step 2 is the explicit detector.

Risk 3 — single-seed factor ranks. Most cells run at seed 42 only; multi-seed coverage is restricted to the top-3 per source. A factor ranked 2nd or 3rd whose true effect is borderline could swap with a 4th-ranked factor under seed noise. We accept this risk because broadening multi-seed to all 32×3 cells multiplies compute by 3× and is out of cost scope.

Risk 4 — F1×F2 pre-registration vs the other 9 interactions. With 10 two-way interactions reported and a single one pre-registered, multiple-comparison hygiene matters. The aggregator labels exploratory interactions accordingly; we do not claim significance for any exploratory interaction without a confirmatory experiment.

Risk 5 — A/B confound on user-message tokens. Even though B is induced by a natural format instruction, the instruction tokens still live inside the user message and could shift attention patterns independent of completion length. This is a genuine confound the screen cannot fully separate; the A×B interaction term is the diagnostic and is pre-registered for that reason.

Critique loop notes. This is a re-finalization of an owner-approved design (the planJson is fully populated and the design body has been stable across multiple rounds). The scientific design is unchanged from the prior approved plan; the only delta is runpod-spec.substitution_policy.account.prefer flipping from "team" to "personal" plus the corresponding addition of kill criterion #6 (bootstrap-silence detector) and Verification step 2. I ran the consistency check internally rather than the full paired-critic loop because (a) the design is owner-approved, (b) the open question is purely whether the runpod-spec matches the patched DB state and the script's CLI contract, and (c) the script's parse_args (marker_factor_screen.py:62-138) was re-verified against each pod's dockerArgs. Loops run: 0 (re-finalize); merged verdict: pass for methodology, statistics, and alternative-explanations because no design field changed; no follow-ups intentionally dropped. If a future revision changes any scientific field, that revision should re-enter the full paired-critic loop.

Likely Clean Result

A body HTML on experiment #365 following docs/clean-result-guidelines.md:

  • TL;DR (single paragraph in first person): "I ran a balanced 2^5 factorial across five marker-implantation factors on three source personas. System-prompt length and loss-mask scope were the two load-bearing knobs, both with Cohen's d > 0.4 on source-rate; persona framing had near-zero independent effect once length was controlled, confirming #340. Long answer-format prompts collapsed source-rate at the extreme, replicating #295. Off-policy data lost ~0.2 d of source-rate vs on-policy at matched length."
  • Primary plot: a single bar chart of the five main-effect Cohen's d's on source-rate with 95% bootstrap CIs, ordered largest-to-smallest, with plain-English axis labels ("system-prompt length", "loss masks marker only", etc.) and SVG <title> hover tooltips carrying the underlying mean and CI.
  • Experimental design dropdown: the 32-cell factor table, the 3-source stratification, the seed plan, the bootstrap scheme, and the kill-criterion list — collapsed by default.

Sections deliberately omitted per the clean-result guidelines: separate Background / Methodology h2s, standing caveats, references to the abandoned single-axis sweeps, and the additional per-source heatmaps (those live as linked figures, not in the body).

Approval Checklist

  • Goal matches the experiment record title and absorbs the open scope of #361 / #339 / #353 / #46.
  • Hypothesis is specific: five factors split into three classes with signed predictions for each.
  • Prediction is falsifiable: numeric Cohen's d thresholds with α=0.05 and a named bootstrap scheme.
  • Kill criterion has six concrete triggers, including the new bootstrap-silence detector that directly responds to the recovery-trigger failure mode.
  • Compute and Hardware estimates 4 × 1 × 18 h × $1.49 ≈ $107 compute + ~$2 storage = ~$110 total at A100 80GB SXM Secure Cloud rates; cost-overrun kill at $160. Multi-pod array is justified under clause (c) per-pod role isolation; consolidation deferred to a future ablation.
  • Artifacts enumerated per-pod and aggregator with /workspace/runs/365/... paths matching the script's directory contract.
  • Verification covers spec parity, the bootstrap-progress detector, Phase 0/1 kill gates, and the aggregator's required JSONs / clean-result HTML.
  • Risks explicitly cover the team-account vanishing failure that triggered this recovery and document the rationale for flipping account.prefer to personal.
  • Likely clean result follows docs/clean-result-guidelines.md (TL;DR → primary plot → design dropdown, first-person voice, no standing caveats).
  • runpod-spec matches the plan: 4 pods, A100 80GB Secure Cloud preferred, single-GPU per pod, account.prefer=personal with team retained in allowed, and per-pod dockerArgs identical to the persisted experiments.077ae4c7…pod_spec save for that one substitution-policy field.
[
  {
    "name": "marker-screen-365-pod0-pre-and-source-librarian",
    "gpuType": "A100",
    "gpuCount": 1,
    "volumeGb": 100,
    "containerDiskGb": 100,
    "cloudType": "SECURE",
    "estimatedMinutes": 1080,
    "env": {
      "SAGAN_EPS_BRANCH": "experiment-365",
      "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7"
    },
    "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 0 --num-pods 4 --source-persona librarian --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --run-pre-screen --run-smoke --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'",
    "config": {
      "command": "Pod 0: Phase 0 base-model contamination pre-screen on 24x20x5 eval panel + Phase 1 8-cell res-III librarian smoke (kill gates only) + Phase 2 32-cell librarian slab at primary seed + Phase 3 multi-seed top-3 librarian cells (seeds 137, 256). Clustered bootstrap (question-clustered SR, persona-clustered LR).",
      "artifacts": [
        "/workspace/runs/365/pod0/pre_screen.json",
        "/workspace/runs/365/pod0/smoke.json",
        "/workspace/runs/365/pod0/librarian/metrics.json",
        "/workspace/runs/365/pod0/librarian/adapters/",
        "/workspace/runs/365/pod0/figures/"
      ]
    },
    "substitution_policy": {
      "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 },
      "gpuCount": { "min": 1, "max": 1 },
      "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" },
      "dataCenterId": { "allowed": "any" },
      "account": { "allowed": ["personal", "team"], "prefer": "personal" },
      "volumeGb": { "min": 100 },
      "containerDiskGb": { "min": 100 }
    },
    "consolidation": {
      "may_merge_pods": false,
      "merge_target_max_gpus_per_pod": 1
    }
  },
  {
    "name": "marker-screen-365-pod1-source-surgeon",
    "gpuType": "A100",
    "gpuCount": 1,
    "volumeGb": 100,
    "containerDiskGb": 100,
    "cloudType": "SECURE",
    "estimatedMinutes": 1080,
    "env": {
      "SAGAN_EPS_BRANCH": "experiment-365",
      "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7"
    },
    "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 1 --num-pods 4 --source-persona surgeon --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'",
    "config": {
      "command": "Pod 1: Phase 2 32-cell surgeon slab at primary seed 42 + Phase 3 multi-seed top-3 surgeon cells (seeds 137, 256). Clustered bootstrap (question-clustered SR, persona-clustered LR).",
      "artifacts": [
        "/workspace/runs/365/pod1/surgeon/metrics.json",
        "/workspace/runs/365/pod1/surgeon/adapters/",
        "/workspace/runs/365/pod1/figures/"
      ]
    },
    "substitution_policy": {
      "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 },
      "gpuCount": { "min": 1, "max": 1 },
      "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" },
      "dataCenterId": { "allowed": "any" },
      "account": { "allowed": ["personal", "team"], "prefer": "personal" },
      "volumeGb": { "min": 100 },
      "containerDiskGb": { "min": 100 }
    },
    "consolidation": {
      "may_merge_pods": false,
      "merge_target_max_gpus_per_pod": 1
    }
  },
  {
    "name": "marker-screen-365-pod2-source-programmer",
    "gpuType": "A100",
    "gpuCount": 1,
    "volumeGb": 100,
    "containerDiskGb": 100,
    "cloudType": "SECURE",
    "estimatedMinutes": 1080,
    "env": {
      "SAGAN_EPS_BRANCH": "experiment-365",
      "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7"
    },
    "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 2 --num-pods 4 --source-persona programmer --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'",
    "config": {
      "command": "Pod 2: Phase 2 32-cell programmer slab at primary seed 42 + Phase 3 multi-seed top-3 programmer cells (seeds 137, 256). Clustered bootstrap (question-clustered SR, persona-clustered LR).",
      "artifacts": [
        "/workspace/runs/365/pod2/programmer/metrics.json",
        "/workspace/runs/365/pod2/programmer/adapters/",
        "/workspace/runs/365/pod2/figures/"
      ]
    },
    "substitution_policy": {
      "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 },
      "gpuCount": { "min": 1, "max": 1 },
      "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" },
      "dataCenterId": { "allowed": "any" },
      "account": { "allowed": ["personal", "team"], "prefer": "personal" },
      "volumeGb": { "min": 100 },
      "containerDiskGb": { "min": 100 }
    },
    "consolidation": {
      "may_merge_pods": false,
      "merge_target_max_gpus_per_pod": 1
    }
  },
  {
    "name": "marker-screen-365-pod3-aggregator-and-overflow",
    "gpuType": "A100",
    "gpuCount": 1,
    "volumeGb": 100,
    "containerDiskGb": 100,
    "cloudType": "SECURE",
    "estimatedMinutes": 1080,
    "env": {
      "SAGAN_EPS_BRANCH": "experiment-365",
      "SAGAN_EPS_COMMIT_SHA": "b1a24b4b04f92598e381fa3cd207a0fe5d24b9e7"
    },
    "dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 3 --num-pods 4 --role aggregator-and-overflow --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --build-figures --write-clean-result --label-f1xf2-preregistered --progress-url \"$SAGAN_PROGRESS_URL\" --progress-token \"$SAGAN_POD_PROGRESS_TOKEN\" --agent-run-id \"$SAGAN_AGENT_RUN_ID\" --experiment-id \"$SAGAN_EXPERIMENT_ID\" --run-index \"$SAGAN_RUN_INDEX\"'",
    "config": {
      "command": "Pod 3: Phase 4 aggregator. Waits up to 24h for pods 0/1/2 metrics.json files, then builds main_effects.json, interactions.json (with A x B pre-registered), the persona x cell heatmap, the factor-ranking bar chart, the A x B interaction plot, and the clean-result HTML attached to experiments.body.",
      "artifacts": [
        "/workspace/runs/365/pod3/main_effects.json",
        "/workspace/runs/365/pod3/interactions.json",
        "/workspace/runs/365/pod3/aggregate_metrics.json",
        "/workspace/runs/365/pod3/figures/persona_cell_heatmap.svg",
        "/workspace/runs/365/pod3/figures/factor_ranking.svg",
        "/workspace/runs/365/pod3/figures/AxB_interaction.svg",
        "/workspace/runs/365/pod3/clean_result.html"
      ]
    },
    "substitution_policy": {
      "gpuType": { "allowed": ["A100", "A100-SXM", "H100", "H200"], "min_vram_gb": 80 },
      "gpuCount": { "min": 1, "max": 1 },
      "cloudType": { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" },
      "dataCenterId": { "allowed": "any" },
      "account": { "allowed": ["personal", "team"], "prefer": "personal" },
      "volumeGb": { "min": 100 },
      "containerDiskGb": { "min": 100 }
    },
    "consolidation": {
      "may_merge_pods": false,
      "merge_target_max_gpus_per_pod": 1
    }
  }
]

Recovery summary. Diagnosed the failure as the recurring team-account post-RUNNING vanishing (Risk 2 from the prior plan). Re-emitted the owner-approved 4-pod plan unchanged except for: (1) substitution_policy.account.prefer flipped from team to personal; (2) kill criterion #6 added as an explicit detector for the same failure mode under the new account; (3) Verification step 2 documents the 5-min bootstrap-progress check. The persisted experiments.077ae4c7…pod_spec already has personal in account.allowed, so this is a scope-preserving recovery, not a design change.

Events

1:26:16 PMstartedagent
kind=apply
1:26:32 PMtool_calltools

tool=Bash

Bash
1:28:34 PMtool_resulttools
Command running in background with ID: bbtrv5399. Output is being written to: /tmp/claude-1001/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475/tasks/bbtrv5399.output. You will be notified when it completes. To check interim output, use Read on that file path.
1:28:38 PMtool_calltools

tool=Bash

Bash
1:30:38 PMtool_resulttools
Command running in background with ID: b3wpniji8. Output is being written to: /tmp/claude-1001/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475/tasks/b3wpniji8.output. You will be notified when it completes. To check interim output, use Read on that file path.
1:30:42 PMtool_calltools

tool=Read

Read
1:30:42 PMtool_resulttools
<system-reminder>Warning: the file exists but is shorter than the provided offset (1). The file has 1 lines.</system-reminder>
1:30:45 PMtool_calltools

tool=Read

Read
1:30:45 PMtool_resulttools
<system-reminder>Warning: the file exists but is shorter than the provided offset (1). The file has 1 lines.</system-reminder>
1:30:50 PMtool_calltools

tool=Bash

Bash
1:32:50 PMtool_resulttools
Command running in background with ID: bvbun5y5r. Output is being written to: /tmp/claude-1001/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475/tasks/bvbun5y5r.output. You will be notified when it completes. To check interim output, use Read on that file path.
1:32:54 PMtool_calltools

tool=Bash

Bash
1:32:54 PMtool_resulttools
---
---
1:32:57 PMtool_calltools

tool=ToolSearch

ToolSearch
1:32:58 PMtool_resulttools
1:33:05 PMtool_calltools

tool=Bash

Bash
1:35:05 PMtool_resulttools
Command running in background with ID: bl24r75nu. Output is being written to: /tmp/claude-1001/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475/tasks/bl24r75nu.output. You will be notified when it completes. To check interim output, use Read on that file path.
1:35:08 PMtool_calltools

tool=Bash

Bash
1:35:13 PMtool_resulttools
-rw-r--r-- 1 thomasjiralerspong thomasjiralerspong 0 May 13 13:33 /tmp/exp.json
0 /tmp/exp.json
1:35:16 PMtool_calltools

tool=Bash

Bash
1:35:16 PMtool_resulttools
(Bash completed with no output)
1:35:19 PMtool_calltools

tool=Bash

Bash
1:35:19 PMtool_resulttools
/home/thomasjiralerspong/sagan
-rw-rw-r-- 1 thomasjiralerspong thomasjiralerspong 1830 May 13 12:29 .env
1:35:24 PMtool_calltools

tool=Bash

Bash
1:35:24 PMtool_resulttools
NEXT_PUBLIC_SITE_URL=<set>
SAGAN_API_TOKEN=<set>
1:35:28 PMtool_calltools

tool=Bash

Bash
1:37:28 PMtool_resulttools
Command running in background with ID: bhhcb7vj3. Output is being written to: /tmp/claude-1001/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475/tasks/bhhcb7vj3.output. You will be notified when it completes. To check interim output, use Read on that file path.
1:37:32 PMtool_calltools

tool=Bash

Bash
1:37:42 PMtool_resulttools
URL=http://localhost:3000
TOKEN_LEN=46
---
-rw-r--r-- 1 thomasjiralerspong thomasjiralerspong 0 May 13 13:33 /tmp/exp.json
1:37:47 PMtool_calltools

tool=Bash

Bash
1:37:49 PMtool_resulttools
HTTP=200 SIZE=242842 TIME=1.457219
{"experiment":{"id":"077ae4c7-e816-4dd8-a150-ad8fe19cb795","number":365,"legacyGhNumber":null,"beliefId":null,"projectId":null,"title":"Factor screen for marker implantation + leakage (2^5: system-prompt length, answer-format length, persona-presence, on-policy, marker-only-loss)","body":"## Motivation\n\nWe want a single experiment that ranks the dominant factors controlling **marker implantation** (source `[ZLT]` rate) and **marker leakage** (mean off-diagonal rate) under LoRA SFT on Qwen2.5-7B-Instruct. Five prior issues varied one axis at a time, with conflicting or co-linear results:\n\n- [#337](https://github.com/superkaiba/explore-persona-space/issues/337) (MODERATE) — longer persona system prompts on the 48-source panel implant more (ρ=+0.38) and leak less (ρ=−0.38), but length and persona-richness co-vary.\n- [#295](https://github.com/superkaiba/explore-persona-space/issues/295) (LOW) — stretching completion length / turn count on a fixed librarian source collapses uptake to 0/100 at the longest setting.\n- [#340](https://github.com/superkaiba/explore-persona-space/issues/340) (MODERATE) — persona-to-assistant cosine has zero independent signal once prompt length is partialled out.\n- [#181](https://github.com/superkaiba/explore-persona-space/issues/181) / [#208](https://github.com/superkaiba/explore-persona-space/issues/208) — non-persona triggers leak broadly under any recipe.\n- [#46](https://github.com/superkaiba/explore-persona-space/issues/46) (appr
1:37:54 PMtool_calltools

tool=Bash

Bash
1:37:54 PMtool_resulttools
number: 365
status: running
plan_status: None
result_status: None
plan_approved_at: None
keys: ['id', 'number', 'legacyGhNumber', 'beliefId', 'projectId', 'title', 'body', 'hypothesis', 'planMd', 'planJson', 'configYaml', 'status', 'kind', 'computeSize', 'priority', 'assigneeKind', 'tags', 'hasCleanResult', 'autoApprovePlan', 'parentExperimentId', 'runpodAccount', 'createdAt', 'updatedAt', 'turn']
1:38:00 PMtool_calltools

tool=Bash

Bash
1:38:00 PMtool_resulttools
--- plan_json snippet ---
{
  "goal": "Quantify how five orthogonal design choices in the EPS marker-implantation recipe affect (i) **source rate** (the `[ZLT]` marker is produced when the trained source persona is active) and (ii) **off-diagonal leakage** (the marker is produced for bystander personas). Identify which of the five factors have main effects \u2265 5 percentage points (pp) on source rate or mean off-diagonal leakage, and whether the pre-registered F1\u00d7F2 interaction is non-negligible (\u2265 5 pp beyond additive). The remaining nine 2-way interactions are exploratory and reported on a heatmap without per-pair pre-registration. Use the screen to fix defaults for the next EPS marker recipe, and to decide whether the un-yoked length factors warrant separate optimization or should be re-yoked at a fixed total length.\n\nThis is a screening experiment, not a confirmation experiment: it ranks factors and flags interactions on a single primary seed, then uses a small multi-seed top-3-per-source replication to put a training-noise band on the strongest cells.",
  "risks": "- **Un-yoked length factors create an absolute-length confound.** The title's 2^5 splits the prior 2^4's single yoked F_A into F1 and F2, so total assistant-message length now varies from ~56 to ~2050 tokens across cells. *Mitigation:* H4 pre-registers the F1\u00d7F2 interaction test as the discriminator, and the clean result reports total-token-count as an analysis covariate (figure iv). If F1\u00d7F2 dominates the additive main effects, the recipe should re-yoke length at a fixed total.\n\n- **F1 main effect is jointly length-and-content.** F1 varies system-prompt length, but at F3=absent F1 varies length of filler while at F3=present F1 varies length of persona-bearing content. *Mitigation:* H3 is worded to acknowledge this; the clean result reports both the F1 main effect and the F1\u00d7F3 interaction so the reader can attribute the F1 signal to length vs. content.\n\n- **F4 on-policy is generator-identity 

--- plan_md snippet ---
All 11 required headings present in order, runpod-spec is valid JSON with 4 pods matching the plan's narrative, cost arithmetic checks out at $194 compute → ~$200 with storage. Emitting the final plan:

---

## Goal

Quantify how five orthogonal design choices in the EPS marker-implantation recipe affect (i) **source rate** (the `[ZLT]` marker is produced when the trained source persona is active) and (ii) **off-diagonal leakage** (the marker is produced for bystander personas). Identify which of the five factors have main effects ≥ 5 percentage points (pp) on source rate or mean off-diagonal leakage, and whether the pre-registered F1×F2 interaction is non-negligible (≥ 5 pp beyond additive). The remaining nine 2-way interactions are exploratory and reported on a heatmap without per-pair pre-registration. Use the screen to fix defaults for the next EPS marker recipe, and to decide whether the un-yoked length factors warrant separate optimization or should be re-yoked at a fixed total length.

This is a screening experiment, not a confirmation experiment: it ranks factors and flags interactions on a single primary seed, then uses a small multi-seed top-3-per-source replication to put a training-noise band on the strongest cells.

## Hypothesis

- **H1 (primary).** Two factors dominate source rate: **marker-only-loss** (F5=marker-only; whole-completion loss F5=full halves source rate) and **on-policy completions** (F4=on increases source rate, because the surrounding-token dist
1:38:07 PMtool_calltools

tool=Bash

Bash
1:38:08 PMtool_resulttools
keys: ['runs']
runs count: 20
2026-05-13T13:33:40.290Z apply      running      id=dc6acaa2 req=Moved to running on the Pipeline board (recovery: plan c9def0e5 was approved but
2026-05-13T13:26:24.935Z apply      completed    id=5ddcaa08 req=[manual-retry-of:c2394f02-7630-400d-9684-ec5b7a87dcd4]

The previous Claude Code
2026-05-13T13:26:23.498Z apply      running      id=b04ab72f req=[manual-retry-of:782b8e70-9c60-4e8f-9b27-ac5b17a9e815]

The previous Claude Code
2026-05-13T13:26:21.762Z apply      running      id=b85431d8 req=[manual-retry-of:f43d96ac-e7dd-4aee-9b7c-ea2190e6371c]

The previous Claude Code
2026-05-13T13:26:19.442Z experiment running      id=6997b572 req=[manual-retry-of:e760e311-bb16-4ac8-9b70-3f66443db556]

The previous Claude Code
2026-05-13T13:26:16.162Z apply      running      id=41a17b33 req=[manual-retry-of:793f0eef-6e83-4359-a0c0-94469d5cfcae]

The previous Claude Code
2026-05-13T13:20:27.693Z experiment completed    id=103d180b req=Moved from idea to clarifying on the Pipeline board.

Clarify the scoped experim
2026-05-13T13:11:01.662Z apply      failed       id=793f0eef req=[auto-recovery-for:64a794c8-1dc0-44f4-9491-3563c3773c1e]

The previous Claude Co
2026-05-13T13:10:42.260Z apply      failed       id=64a794c8 req=experiment-orchestrator-for:3ccf4de3-57e2-4e55-a32c-9a58399093cf

Drive experime
2026-05-13T13:10:30.288Z experiment failed       id=e760e311 req=[auto-recovery-for:c8084fe4-0c49-45b5-94e3-f29fe89907ef]

The previous Claude Co
2026-05-13T13:10:30.054Z apply      failed       id=77932968 req=[auto-recovery-for:9cb3275e-e1a5-4f6e-b16c-2d284240cce3]

The previous Claude Co
2026-05-13T13:10:30.020Z apply      failed       id=782b8e70 req=[auto-recovery-for:9cb3275e-e1a5-4f6e-b16c-2d284240cce3]

The previous Claude Co
2026-05-13T13:10:30.001Z apply      failed       id=f43d96ac req=[auto-recovery-for:5bb80a98-9f5b-4e5b-a86c-e3dc51405a39]

The previous Claude Co
2026-05-13T13:10:29.343Z apply      failed       id=c2394f02 req=[auto-recovery-for:8041b150-c6ce-47f5-b946-ca30df6074ad]

The previous Claude Co
2026-05-13T13:09:46.529Z experiment failed       id=c8084fe4 req=Moved from awaiting_clarifications to planning on the Pipeline board.

Draft the
2026-05-13T13:07:55.606Z apply      failed       id=5bb80a98 req=experiment-orchestrator-for:aeadf14b-ea01-49ee-961f-23893d58b725

Drive experime
2026-05-13T13:04:32.101Z experiment completed    id=aeadf14b req=Moved from awaiting_clarifications to planning on the Pipeline board.

Draft the
2026-05-13T13:03:31.092Z qa         completed    id=a7a3fed3 req=Comment responder: Claude

Entity: experiment 077ae4c7-e816-4dd8-a150-ad8fe19cb7
2026-05-13T13:01:05.106Z apply      failed       id=9cb3275e req=experiment-orchestrator-for:e1baedab-da61-4b4e-8355-f46936f0f788

Drive experime
2026-05-13T13:01:04.831Z experiment completed    id=e1baedab req=[plan-reused-from:a1f04a02-f418-461b-904c-0b05d29528d1]

Approved an existing pl
1:38:20 PMtool_calltools

tool=Bash

Bash
1:38:20 PMtool_resulttools
=== run dc6acaa2 ===
Traceback (most recent call last):
  File "<string>", line 3, in <module>
  File "/usr/lib/python3.10/json/__init__.py", line 293, in load
    return loads(fp.read(),
  File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/usr/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.10/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
=== run 6997b572 ===
Traceback (most recent call last):
  File "<string>", line 3, in <module>
  File "/usr/lib/python3.10/json/__init__.py", line 293, in load
    return loads(fp.read(),
  File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/usr/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.10/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
1:38:24 PMtool_calltools

tool=Bash

Bash
1:38:24 PMtool_resulttools
HTTP=500
1:38:31 PMtool_calltools

tool=Bash

Bash
1:38:31 PMtool_resulttools
FULL_ID: dc6acaa2-5e65-4f59-a848-e43adb533829
kind: apply
status: running
createdAt: 2026-05-13T13:33:40.290Z
updatedAt: 2026-05-13T13:38:28.655Z
runpod_pod_id: None
plan_md_len: 0
result_md_len: 0
request[:500]: Moved to running on the Pipeline board (recovery: plan c9def0e5 was approved but never dispatched an apply because handleApprovedRun finalizes todo-scoped plans without queueing the implementer).

Advance this task now: "Use Tinker (Thinking Machines Lab) + adjacent libraries to optimize fine-tuning recipes". Use the scoped task context and make the smallest useful change or report the exact blocker.
keys: ['id', 'kind', 'provider', 'status', 'request', 'planMd', 'planJson', 'approvalRequired', 'approvedBy', 'approvedAt', 'scopeEntityKind', 'scopeEntityId', 'chatSessionId', 'branchName', 'vercelDeploymentUrl', 'runpodAccount', 'runpodPodId', 'runpodPodIds', 'runpodStatus', 'transcriptLogPath', 'changedFilesJson', 'lastError', 'startedAt', 'completedAt', 'createdAt', 'updatedAt']
1:38:39 PMtool_calltools

tool=Bash

Bash
1:38:39 PMtool_resulttools
analyzer.md
clean-result-critic.md
code-reviewer.md
codex-clean-result-critic.md
codex-code-reviewer.md
codex-interpretation-critic.md
consistency-checker.md
experiment-implementer.md
experiment-planner.md
experimenter.md
follow-up-proposer.md
interpretation-critic.md
reconciler.md
upload-verifier.md
uploader.md
---skills---
issue
1:38:42 PMtool_calltools

tool=Bash

Bash
1:38:42 PMtool_resulttools
SKILL.md
markers.md
1:38:45 PMtool_calltools

tool=Read

Read
1:38:45 PMtool_resulttools
1	# /issue
2	
3	Use this skill when the user says `/issue <N>` or asks an agent to work an
4	experiment workflow item by number.
5	
6	`<N>` is `experiments.number` in Sagan. It is not a GitHub issue number.
7	GitHub issues, labels, comments, and project-board columns are historical
8	evidence only and must not be used as workflow state.
9	
10	## Required Setup
11	
12	Read workflow state through:
13	
14	```bash
15	python scripts/sagan_state.py view <N>
16	```
17	
18	Mutate workflow state only through `scripts/sagan_state.py`, which calls the
19	Sagan HTTP API with `Authorization: Bearer $SAGAN_API_TOKEN`.
20	
21	## Workflow
22	
23	1. Load the Sagan experiment by number.
24	2. If the status is `proposed`, move to `clarifying` or record why
25	   clarification is unnecessary.
26	3. During `clarifying`, establish only:
27	   - the specific hypothesis;
28	   - expected information gain;
29	   - what result would change the next action or belief;
30	   - any missing constraint that would make planning invalid.
31	4. If those points are already clear, move to `planning`.
32	5. Use `plan_pending` for owner approval, `approved`/`queued` for launch,
33	   `running`/`uploading`/`verifying` for runtime and artifact handling,
34	   `interpreting`/`reviewing` for analysis and critique, and
35	   `awaiting_promotion` before final promotion to `completed`.
36	
37	## Commands
38	
39	Set status:
40	
41	```bash
42	python scripts/sagan_state.py status <N> clarifying --note "Need hypothesis and information gain."
43	```
44	
45	Patch metadata:
46	
47	```bash
48	python scripts/sagan_state.py patch <N> --title "..." --hypothesis-file /tmp/hypothesis.md --tags "eps,geometry"
49	```
50	
51	Post marker:
52	
53	```bash
54	python scripts/sagan_state.py marker <N> epm:clarify --to-status planning --note "Hypothesis and information gain are clear."
55	```
56	
57	Promote result:
58	
59	```bash
60	python scripts/sagan_state.py promote <N> useful --note "Clean result accepted."
61	```
62	
63	Patch a clean result:
64	
65	```bash
66	python scripts/sagan_state.py clean-result <uuid> --status reviewing
67	```
68	
69	## Reviewer Loop
70	
71	For code review, interpretation critique, and clean-result critique, run the
72	Claude/Codex pair for at most three rounds. Post every reviewer verdict and
73	reconciler decision as `workflow_events` with reviewer metadata.
74	
75	Round-3 rule: if reviewers still disagree after round 3, the reconciler writes
76	the final critique, applies or requests only the minimal necessary fix, and the
77	workflow continues unless there is a true user-decision blocker such as missing
78	owner input, unsafe execution, invalid artifacts, or an untestable hypothesis.
79	
80	See `markers.md` for marker names and metadata shape.
81	
1:38:48 PMtool_calltools

tool=Bash

Bash
1:38:48 PMtool_resulttools
/bin/bash: line 4: python: command not found
1:38:52 PMtool_calltools

tool=Bash

Bash
1:39:22 PMtool_resulttools
Traceback (most recent call last):
  File "/home/thomasjiralerspong/sagan/scripts/sagan_state.py", line 356, in <module>
    raise SystemExit(main())
  File "/home/thomasjiralerspong/sagan/scripts/sagan_state.py", line 348, in main
    args.func(args)
  File "/home/thomasjiralerspong/sagan/scripts/sagan_state.py", line 160, in cmd_view
    print_json(by_number(args, args.number))
  File "/home/thomasjiralerspong/sagan/scripts/sagan_state.py", line 141, in by_number
    return request(args, "GET", f"/api/experiments/by-number/{number}")
  File "/home/thomasjiralerspong/sagan/scripts/sagan_state.py", line 94, in request
    with urllib.request.urlopen(req, timeout=args.timeout) as res:
  File "/usr/lib/python3.10/urllib/request.py", line 216, in urlopen
    return opener.open(url, data, timeout)
  File "/usr/lib/python3.10/urllib/request.py", line 519, in open
    response = self._open(req, data)
  File "/usr/lib/python3.10/urllib/request.py", line 536, in _open
    result = self._call_chain(self.handle_open, protocol, protocol +
  File "/usr/lib/python3.10/urllib/request.py", line 496, in _call_chain
    result = func(*args)
  File "/usr/lib/python3.10/urllib/request.py", line 1377, in http_open
    return self.do_open(http.client.HTTPConnection, req)
  File "/usr/lib/python3.10/urllib/request.py", line 1352, in do_open
    r = h.getresponse()
  File "/usr/lib/python3.10/http/client.py", line 1395, in getresponse
    response.begin()
  File "/usr/lib/python3.10/http/client.py", line 323, in begin
    version, status, reason = self._read_status()
  File "/usr/lib/python3.10/http/client.py", line 284, in _read_status
    line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1")
  File "/usr/lib/python3.10/socket.py", line 705, in readinto
    return self._sock.recv_into(b)
TimeoutError: timed out
1:39:26 PMtool_calltools

tool=Bash

Bash
1:39:26 PMtool_resulttools
6:  SAGAN_BASE_URL=https://sagan.superkaiba.com
67:def base_url(args: argparse.Namespace) -> str:
68:    value = args.base_url or os.environ.get("SAGAN_BASE_URL") or os.environ.get("NEXT_PUBLIC_SITE_URL")
70:        value = "http://localhost:3100"
84:        f"{base_url(args)}{path}",
102:    print(json.dumps(value, indent=2, sort_keys=True, default=str))
264:    parser.add_argument("--base-url", help="Sagan base URL; defaults to SAGAN_BASE_URL or NEXT_PUBLIC_SITE_URL")
265:    parser.add_argument("--token", help="Bearer token; defaults to SAGAN_API_TOKEN")
266:    parser.add_argument("--timeout", type=int, default=30)
271:    p.add_argument("--limit", type=int, default=100)
272:    p.set_defaults(func=cmd_list)
276:    p.set_defaults(func=cmd_view)
282:    p.set_defaults(func=cmd_status)
299:    p.set_defaults(func=cmd_patch)
304:    p.add_argument("--event-type", default="note")
309:    p.add_argument("--actor-kind", default="agent")
317:    p.set_defaults(func=cmd_marker)
323:    p.set_defaults(func=lambda args: (setattr(args, "verdict", args.verdict.replace("-", "_")), cmd_promote(args))[1])
330:    p.set_defaults(func=cmd_launch_pod)
340:    p.set_defaults(func=cmd_clean_result)
1:39:29 PMtool_calltools

tool=Bash

Bash
1:39:30 PMtool_resulttools
<persisted-output>
Output too large (102.6KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475/tool-results/b0hwenjl5.txt

Preview (first 2KB):
{
  "approvalRequests": [
    {
      "agentRunId": null,
      "approvedState": "approved",
      "bodyMd": null,
      "createdAt": "2026-05-13T11:55:30.960Z",
      "entityId": "077ae4c7-e816-4dd8-a150-ad8fe19cb795",
      "entityKind": "experiment",
      "experimentId": "077ae4c7-e816-4dd8-a150-ad8fe19cb795",
      "id": "a2133918-8cf4-44ee-90ce-20777f84483d",
      "kind": "experiment_plan",
      "metadata": null,
      "rejectedState": "planning",
      "requestedBy": "660cff98-a4cc-4b4f-9afc-334516773855",
      "requestedState": "plan_pending",
      "resolvedAt": "2026-05-13T13:10:41.834Z",
      "resolvedBy": "660cff98-a4cc-4b4f-9afc-334516773855",
      "resolvedNote": "Approved from Pipeline board after moving to queued.",
      "status": "approved",
      "title": "Approve experiment plan: Factor screen for marker implantation + leakage (2^5: system-prompt length, answer-format length, persona-presence, on-policy, marker-only-loss)",
      "updatedAt": "2026-05-13T13:10:41.834Z"
    },
    {
      "agentRunId": "2788dd4e-7607-4970-aca2-d8630c106e1b",
      "approvedState": "approved",
...
</persisted-output>
1:39:37 PMtool_calltools

tool=Bash

Bash
1:39:37 PMtool_resulttools
STATUS: running
KIND: experiment
TITLE: Factor screen for marker implantation + leakage (2^5: system-prompt length, answer-format length, persona-presence, on-p
HAS_PLAN_MD: True
HAS_CLEAN_RESULT: False
--workflow events--

--clean results--

--approval requests--
  status=approved kind=experiment_plan requestedState=plan_pending resolvedNote=Approved from Pipeline board after moving to queued.
  status=approved kind=experiment_plan requestedState=plan_pending resolvedNote=Approved from Pipeline board after moving to running.
  status=approved kind=experiment_plan requestedState=plan_pending resolvedNote=Approved from Pipeline board after moving to queued.
1:39:43 PMtool_calltools

tool=Bash

Bash
1:39:43 PMtool_resulttools
TOP KEYS: ['approvalRequests', 'events', 'experiment']

--agent runs--

--events--
  2026-05-13T11:55:30 type=state_changed  
  2026-05-13T11:55:29 type=state_changed  
  2026-05-13T11:27:07 type=state_changed  
  2026-05-13T11:26:48 type=state_changed  
  2026-05-13T11:26:45 type=state_changed  
  2026-05-13T11:26:45 type=state_changed  
  2026-05-13T11:25:35 type=approval_requested 
  2026-05-13T11:25:35 type=state_changed  
  2026-05-13T11:21:46 type=state_changed  
  2026-05-13T11:19:35 type=state_changed  
  2026-05-13T10:51:20 type=state_changed  
  2026-05-13T10:51:05 type=state_changed  
  2026-05-13T10:51:03 type=state_changed  
  2026-05-13T10:51:03 type=state_changed  
  2026-05-13T08:10:42 type=note           
  2026-05-13T07:46:50 type=note           
  2026-05-13T07:40:05 type=note           
  2026-05-13T07:37:47 type=note           
  2026-05-13T07:24:11 type=note           
  2026-05-13T04:39:03 type=approval_requested 
  2026-05-13T04:39:03 type=state_changed  
  2026-05-13T04:37:14 type=state_changed  
  2026-05-13T04:37:13 type=blocked        
  2026-05-13T04:21:08 type=state_changed  
  2026-05-12T19:18:15 type=created
1:39:48 PMtool_calltools

tool=Bash

Bash
1:39:48 PMtool_resulttools
---
time: 2026-05-13T10:51:03.159Z
type: state_changed
actor: user
data: None
summary: None
---
time: 2026-05-13T08:10:42.468Z
type: note
actor: codex
data: None
summary: None
---
time: 2026-05-13T07:46:50.611Z
type: note
actor: codex
data: None
summary: None
---
time: 2026-05-13T07:40:05.152Z
type: note
actor: codex
data: None
summary: None
---
time: 2026-05-13T07:37:47.054Z
type: note
actor: codex
data: None
summary: None
---
time: 2026-05-13T07:24:11.681Z
type: note
actor: codex
data: None
summary: None
---
time: 2026-05-13T04:39:03.677Z
type: approval_requested
actor: runner
data: None
summary: None
---
time: 2026-05-13T04:39:03.472Z
type: state_changed
actor: runner
data: None
summary: None
---
time: 2026-05-13T04:37:14.070Z
type: state_changed
actor: runner
data: None
summary: None
---
time: 2026-05-13T04:37:13.284Z
type: blocked
actor: runner
data: None
summary: None
---
time: 2026-05-13T04:21:08.589Z
type: state_changed
actor: user
data: None
summary: None
---
time: 2026-05-12T19:18:15.021Z
type: created
actor: user
data: None
summary: None
1:40:10 PMtool_calltools

tool=Bash

Bash
1:40:11 PMtool_resulttools
Total runs: 50
Running: 5
  2026-05-13T13:33:40 kind=apply      id=dc6acaa2 pod=- req=Moved to running on the Pipeline board (recovery: plan c9def0e5 was approved but
  2026-05-13T13:26:23 kind=apply      id=b04ab72f pod=- req=[manual-retry-of:782b8e70-9c60-4e8f-9b27-ac5b17a9e815]

The previous Claude Code
  2026-05-13T13:26:21 kind=apply      id=b85431d8 pod=- req=[manual-retry-of:f43d96ac-e7dd-4aee-9b7c-ea2190e6371c]

The previous Claude Code
  2026-05-13T13:26:19 kind=experiment id=6997b572 pod=- req=[manual-retry-of:e760e311-bb16-4ac8-9b70-3f66443db556]

The previous Claude Code
  2026-05-13T13:26:16 kind=apply      id=41a17b33 pod=- req=[manual-retry-of:793f0eef-6e83-4359-a0c0-94469d5cfcae]

The previous Claude Code

Unique pods ever associated: 1
pods: ['tvzem3915wzi60']
1:40:18 PMtool_calltools

tool=Bash

Bash
1:40:18 PMtool_resulttools
=== dc6acaa2-5e65-4f59-a848-e43adb533829
kind: apply
scope: todo bd113586-937d-4e74-a90e-c07dd18a8ab6
startedAt: 2026-05-13T13:33:58.362Z
updatedAt: 2026-05-13T13:39:58.658Z
createdAt: 2026-05-13T13:33:40.290Z
full req:
Moved to running on the Pipeline board (recovery: plan c9def0e5 was approved but never dispatched an apply because handleApprovedRun finalizes todo-scoped plans without queueing the implementer).

Advance this task now: "Use Tinker (Thinking Machines Lab) + adjacent libraries to optimize fine-tuning recipes". Use the scoped task context and make the smallest useful change or report the exact blocker.

=== b04ab72f-68bf-42a7-9a3a-0b12cef5b366
kind: apply
scope: experiment 0c120ea3-746a-43e6-a760-e6112f8cb649
startedAt: 2026-05-13T13:26:23.568Z
updatedAt: 2026-05-13T13:39:54.287Z
createdAt: 2026-05-13T13:26:23.498Z
full req:
[manual-retry-of:782b8e70-9c60-4e8f-9b27-ac5b17a9e815]

The previous Claude Code run ended without completing. Pick up where it left off — do not redo work that already finished cleanly.

Original request:
[auto-recovery-for:9cb3275e-e1a5-4f6e-b16c-2d284240cce3]

The previous Claude Code run failed or crashed.

First diagnose why it stopped using the transcript below. Then fix or work around the problem if possible and continue the original request to a final useful result. Do not repeat complet

=== b85431d8-3186-4a36-bd75-e83db881e61f
kind: apply
scope: experiment e37c4633-c442-40d8-a545-c427e59a4b12
startedAt: 2026-05-13T13:26:21.794Z
updatedAt: 2026-05-13T13:39:52.384Z
createdAt: 2026-05-13T13:26:21.762Z
full req:
[manual-retry-of:f43d96ac-e7dd-4aee-9b7c-ea2190e6371c]

The previous Claude Code run ended without completing. Pick up where it left off — do not redo work that already finished cleanly.

Original request:
[auto-recovery-for:5bb80a98-9f5b-4e5b-a86c-e3dc51405a39]

The previous Claude Code run failed or crashed.

First diagnose why it stopped using the transcript below. Then fix or work around the problem if possible and continue the original request to a final useful result. Do not repeat complet

=== 6997b572-ed61-43a2-b7b2-f685994c0ed0
kind: experiment
scope: experiment 3283d57a-7845-4fb7-945c-6e654f7000dd
startedAt: 2026-05-13T13:26:19.471Z
updatedAt: 2026-05-13T13:39:50.082Z
createdAt: 2026-05-13T13:26:19.442Z
full req:
[manual-retry-of:e760e311-bb16-4ac8-9b70-3f66443db556]

The previous Claude Code run ended without completing. Pick up where it left off — do not redo work that already finished cleanly.

Original request:
[auto-recovery-for:c8084fe4-0c49-45b5-94e3-f29fe89907ef]

The previous Claude Code run failed or crashed.

First diagnose why it stopped using the transcript below. Then fix or work around the problem if possible and continue the original request to a final useful result. Do not repeat complet

=== 41a17b33-661a-4cb7-80f2-3a52edf0a6ca
kind: apply
scope: experiment 077ae4c7-e816-4dd8-a150-ad8fe19cb795
startedAt: 2026-05-13T13:26:16.197Z
updatedAt: 2026-05-13T13:40:16.519Z
createdAt: 2026-05-13T13:26:16.162Z
full req:
[manual-retry-of:793f0eef-6e83-4359-a0c0-94469d5cfcae]

The previous Claude Code run ended without completing. Pick up where it left off — do not redo work that already finished cleanly.

Original request:
[auto-recovery-for:64a794c8-1dc0-44f4-9491-3563c3773c1e]

The previous Claude Code run failed or crashed.

First diagnose why it stopped using the transcript below. Then fix or work around the problem if possible and continue the original request to a final useful result. Do not repeat complet
1:40:30 PMtool_calltools

tool=Bash

Bash
1:40:30 PMtool_resulttools
---
name: experiment-implementer
description: >
  Writes the experiment-specific code for a single Sagan experiment: training-script
  edits, Hydra configs, data-generation tweaks, eval-pipeline wiring. Spawned by
  the `/issue` skill after plan approval, before any pod is touched. Pairs with
  `code-reviewer` for independent review. Distinct from `implementer` (standalone
  infra) and from `experimenter` (pod ops + monitoring).
model: opus
skills:
  - codebase-debugger
  - cleanup
memory: project
effort: xhigh
---

# Experiment Implementer

You write the code that an experiment needs. You do NOT run it on a pod — that
is the `experimenter` agent's job. You do NOT do standalone infra refactors —
that is the `implementer` agent's job.

Concretely, your scope for a `type:experiment` issue is:
- Training-script edits (`scripts/train.py`, `scripts/run_sweep.py`)
- Hydra config files (`configs/condition/*.yaml`, `configs/training/*.yaml`,
  `configs/eval/*.yaml`)
- Data-generation / dataset-build scripts when the experiment needs new data
- Eval-pipeline wiring (`src/explore_persona_space/eval/*`)
- Anything else the approved plan calls out as a code change

You are always invoked by the `/issue` skill in **subagent mode** with a
structured brief (the approved plan + worktree path + branch + experiment number).
There is no main-agent mode for this role — if the user wants to pair-program,
they invoke `implementer` directly.

---

## Execution Protocol

### Brief shape (what `/issue` gives you)

- The approved plan (cached at `.claude/plans/issue-<N>.md`)
- Issue number `<N>`
- Worktree path `.claude/worktrees/issue-<N>` and branch `issue-<N>`
- Required `report-back` fields
- Critique history (only present on revision rounds: `epm:code-review v<m>`
  comments to address)

### Before writing code

1. **Read the plan in full.** The reproducibility card is the spec — every
   parameter listed there must be reachable through the code you write
   (config defaults, CLI overrides, or hard-coded values that match the card).
2. **Read the existing code you're modifying.** Do NOT guess function
   signatures, Hydra composition order, or callback hooks. Skim `scripts/train.py`,
   the relevant `configs/condition/*.yaml`, and the periodic-eval callbacks
   before touching anything.
3. **List assumptions** about: library APIs (TRL, PEFT, Transformers), config
   defaults, dataset formats, callback ordering. Mark confidence (high / medium
   / low). For anything below high, verify by reading source or `context7` MCP.
1:40:33 PMtool_calltools

tool=Bash

Bash
1:40:33 PMtool_resulttools
4:experiment workflow item by number.
8:evidence only and must not be used as workflow state.
12:Read workflow state through:
18:Mutate workflow state only through `scripts/sagan_state.py`, which calls the
24:2. If the status is `proposed`, move to `clarifying` or record why
32:5. Use `plan_pending` for owner approval, `approved`/`queued` for launch,
39:Set status:
42:python scripts/sagan_state.py status <N> clarifying --note "Need hypothesis and information gain."
54:python scripts/sagan_state.py marker <N> epm:clarify --to-status planning --note "Hypothesis and information gain are clear."
66:python scripts/sagan_state.py clean-result <uuid> --status reviewing
72:Claude/Codex pair for at most three rounds. Post every reviewer verdict and
73:reconciler decision as `workflow_events` with reviewer metadata.
75:Round-3 rule: if reviewers still disagree after round 3, the reconciler writes
77:workflow continues unless there is a true user-decision blocker such as missing
1:40:37 PMtool_calltools

tool=Read

Read
1:40:37 PMtool_resulttools
1	# Sagan Workflow Markers
2	
3	Markers are Sagan `workflow_events` rows. Do not post GitHub comments, edit
4	GitHub labels, move GitHub project cards, write local state files, or write
5	directly to the Sagan database.
6	
7	Use the HTTP client:
8	
9	```bash
10	python scripts/sagan_state.py marker <experiment_number> epm:plan --note "Plan drafted"
11	```
12	
13	Canonical markers:
14	
15	- `epm:clarify`
16	- `epm:plan`
17	- `epm:code-review`
18	- `epm:code-review-codex`
19	- `epm:review-reconcile`
20	- `epm:preflight`
21	- `epm:launch`
22	- `epm:progress`
23	- `epm:results`
24	- `epm:upload-verification`
25	- `epm:interpretation`
26	- `epm:interp-critique`
27	- `epm:interp-critique-codex`
28	- `epm:clean-result-critique`
29	- `epm:clean-result-critique-codex`
30	- `epm:completion-audit`
31	- `epm:done`
32	- `epm:failure`
33	
34	Reviewer-loop metadata is compact JSON:
35	
36	```json
37	{
38	  "review_pair": "interpretation",
39	  "round": 2,
40	  "reviewer": "codex-interpretation-critic",
41	  "verdict": "needs_targeted_fix",
42	  "required_fix": "Clarify whether the result supports the stated hypothesis."
43	}
44	```
45	
46	Allowed `review_pair` values are `code_review`, `interpretation`, and
47	`clean_result`. Rounds are `1`, `2`, or `3`. Allowed verdicts are `pass`,
48	`needs_targeted_fix`, `blocked_needs_user_decision`, and
49	`fail_not_worth_continuing`.
50	
51	After round 3, reviewer disagreement alone cannot block the experiment. The
52	reconciler records the final critique, chooses the minimal necessary fix, and
53	continues unless the missing input is a real user-decision blocker.
54	
1:40:43 PMtool_calltools

tool=Bash

Bash
1:40:43 PMtool_resulttools
TOP KEYS: ['experiment', 'events', 'approvalRequests']
full ek: ['id', 'number', 'legacyGhNumber', 'beliefId', 'projectId', 'title', 'body', 'hypothesis', 'planMd', 'planJson', 'configYaml', 'status', 'kind', 'computeSize', 'priority', 'assigneeKind', 'tags', 'hasCleanResult', 'autoApprovePlan', 'parentExperimentId', 'runpodAccount', 'createdAt', 'updatedAt', 'turn']
1:40:48 PMtool_calltools

tool=Bash

Bash
1:40:49 PMtool_resulttools
---
Event types: Counter({'state_changed': 22, 'note': 5, 'approval_requested': 3, 'blocked': 2, 'created': 1})
1:40:54 PMtool_calltools

tool=Bash

Bash
1:40:54 PMtool_resulttools
ls: cannot access '.claude/plans/': No such file or directory
---
ls: cannot access '.claude/worktrees/': No such file or directory
1:40:58 PMtool_calltools

tool=Bash

Bash
1:40:59 PMtool_resulttools
---
1:41:01 PMtool_calltools

tool=ToolSearch

ToolSearch
1:41:01 PMtool_resulttools
1:41:06 PMtool_calltools

tool=TodoWrite

TodoWrite
1:41:06 PMtool_resulttools
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
1:41:09 PMtool_calltools

tool=Bash

Bash
1:41:10 PMtool_resulttools
---branch---
main
---log---
65d7e5e Externalize runner prompts so prompt edits skip the runner restart
4c7861a pipeline/advance: kind-aware dedup so a pending plan does not block an apply
8bc3d7e Runner systemd: allow writes to the EPS client repo
13e7318 [TEXTBOX] inline-answer markers: render + persist owner input
cf52836 Runner: cap concurrent runs at 20 + back-pressure on cgroup memory
1:41:15 PMtool_calltools

tool=Bash

Bash
1:41:15 PMtool_resulttools
VM_ORGANIZATION_PLAN.md
claude-code-workflow
dotfiles
eps-dashboard-runs
errors.log
evolving_assistant
explore-persona-space
explore-persona-space-dashboard
housing_search
introsp
make-evil-dumb
nltk_data
noticing-the-watcher
openclaw-migration
personal-assistant
sagan
sandbox_ai_website
skills-staging
snap
1:41:19 PMtool_calltools

tool=Bash

Bash
1:41:32 PMtool_resulttools
/home/thomasjiralerspong/explore-persona-space
---branch---
main
---log---
a4652b62 Route EPS workflow state through Sagan
4129f88d Add Sagan pod progress reporting guidance
d0db2db7 Complete Sagan workflow migration
3c307bd7 WIP catch-up: agent memory, agent-spec edits, external/* updates, experiment results, scripts
22d1913c Sagan-migration audit: port four GitHub-writing scripts + skills to Sagan API; normalize status enum to snake_case
---ls---
agent-memory
agents
cache
mcp.json
plans
rules
settings.json
settings.local.json
skills
workflow.yaml
worktrees
---issue365---
Shell cwd was reset to /home/thomasjiralerspong/sagan
1:41:36 PMtool_calltools

tool=Bash

Bash
1:41:36 PMtool_resulttools
---plans---
---worktrees---
issue-102
issue-112
issue-125
issue-127
issue-138
issue-139
issue-140
issue-150
issue-156
issue-157
issue-162
issue-170
issue-172
issue-176
issue-181
issue-186
issue-188
issue-190
issue-201
issue-203
issue-205
issue-213
issue-218
issue-224
issue-226
issue-228
issue-238
issue-240
issue-246
issue-247
issue-257
issue-260
issue-261
issue-262
issue-263
issue-267
issue-269
issue-274
issue-275
issue-280
issue-296
issue-311
issue-331
issue-344
issue-354
issue-368
issue-61
refactor-codebase-cleanup
workflow-audit-fixes
1:41:50 PMtool_calltools

tool=Bash

Bash
1:41:51 PMtool_resulttools
HTTP=404
<!DOCTYPE html><html lang="en" class="geistsans_d5a4f12f-module__Ur3q_a__variable geistmono_157ca88a-module__iaM1Ya__variable inter_tight_8f18ed7a-module__13eLwq__variable bricolage_grotesque_8c519202-module__UFQ6Tq__variable outfit_333574c6-module__a01f3W__variable manrope_9e067a5b-module__vT7MWq__variable space_grotesk_59d6dcf5-module__z_Ctiq__variable dm_sans_34a85c05-module__gGo3DG__variable ibm_plex_sans_5af3dae-module__edw7da__variable source_serif_4_4203f07b-module__9jTnnG__variable newsreader_4bcebf04-module__mRJj1G__variable"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1, viewport-fit=cover"/><link rel="stylesheet" href="/_next/static/chunks/077y67un5gy30.css" data-precedence="next"/><link rel="preload" as="script" fetchPriority="low" href="/_next/static/chunks/03edqrb4zdj~g.js"/><script src="/_next/static/chunks/0i0b4ibyj497c.js" async=""></script><script src="/_next/static/chunks/0h69mj-e-ya89.js" async=""></script><script src="/_next/static/chunks/014~e0vao-h-9.js" async=""></script><script src="/_next/static/chunks/0pqt~8bl3ukh4.js" async=""></script><script src="/_next/static/chunks/turbopack-14pofyvch95c_.js" async=""></script><script src="/_next/static/chunks/01xlw8hd842-c.js" async=""></script><script src="/_next/static/chunks/0hs1bisaa29...js" async=""></script><meta name="robots" content="noindex"/><meta name="next-size-adjust" content=""/><title>404: This page could not be found.</title><meta name="theme-color" content="#ffffff" media="(prefers-color-scheme: light)"/><meta name="theme-color" content="#16172e" media="(prefers-color-scheme: dark)"/><title>Sagan</title><meta name="description" content="Personal research-life dashboard."/><link rel="manifest" href="/manifest.webmanifest"/><meta name="mobile-web-app-capable" content="yes"/><meta name="apple-mobile-web-app-title" content="Sagan"/><meta name="apple-mobile-web-app-status-bar-style" content="default"/><script>
(() => {
  try {
    const ch
1:42:05 PMtool_calltools

tool=Bash

Bash
1:42:05 PMtool_resulttools
analyzer.md
clean-result-critic.md
code-reviewer.md
codex-clean-result-critic.md
codex-code-reviewer.md
codex-critic.md
codex-interpretation-critic.md
codex-reviewer.md
consistency-checker.md
critic.md
experiment-implementer.md
experimenter.md
follow-up-proposer.md
implementer.md
interpretation-critic.md
manager.md.deprecated
planner.md
reconciler.md
research-pm.md
retrospective.md
reviewer.md
upload-verifier.md
uploader.md
---
1:42:23 PMtool_calltools

tool=Bash

Bash
1:42:23 PMtool_resulttools
---
name: issue
description: >
  End-to-end Sagan experiment workflow for Explore Persona Space. `/issue <N>`
  takes a Sagan `experiments.number`, reads state from Sagan HTTP APIs, posts
  `epm:*` workflow events, and advances the EPS experiment lifecycle without
  using any external tracker as workflow state.
user_invocable: true
---

# /issue

Use this skill when the user says `/issue <N>` or asks an agent to work an
experiment workflow item by number.

`<N>` is `experiments.number` in Sagan. It is not any external tracker number.
External tracker records are historical evidence only and must not be used as
workflow state.

## State Backend

All durable state lives in Sagan:

- `experiments.status` for lifecycle;
- `workflow_events` for `epm:*` markers, approvals, reviewer verdicts, and
  reconciler decisions;
- `agent_runs`, `runs`, `pod_lifecycle`, and artifact records for execution;
- Sagan clean-result promotion for final classification.

Read and mutate state only through `scripts/sagan_state.py`, which calls the
Sagan HTTP API with `Authorization: Bearer $SAGAN_API_TOKEN`.

Useful commands:

```bash
python scripts/sagan_state.py view <N>
python scripts/sagan_state.py set-status <N> clarifying --note "Need hypothesis and information gain."
python scripts/sagan_state.py set-title <N> "New title"
python scripts/sagan_state.py set-body <N> --file /tmp/body.md
python scripts/sagan_state.py add-tag <N> eps
python scripts/sagan_state.py post-marker <N> epm:clarify --note "Hypothesis and information gain are clear."
python scripts/sagan_state.py promote <N> useful
```

## Workflow

1. Load the Sagan experiment by number.
2. If status is `proposed`, move to `clarifying` or record why clarification is
   unnecessary.
3. During `clarifying`, establish only the specific hypothesis, expected
   information gain, what result would change the next action or belief, and
   any missing constraint that would make planning invalid.
4. If those points are already clear, move to `planning`.
5. Use `plan_pending` for owner approval, `approved`/`queued` for launch,
   `running`/`uploading`/`verifying` for runtime and artifact handling,
   `interpreting`/`reviewing` for analysis and critique, and
   `awaiting_promotion` before final promotion to `completed`.

All transitions must post an `epm:*` marker as a Sagan `workflow_events` row.
Do not write local state files as the source of truth.

## Reviewer Pairs

For code review, interpretation critique, and clean-result critique, run the
Claude/Codex pair for at most three rounds. Post every reviewer verdict and
reconciler decision as `workflow_events` with reviewer metadata.

Allowed verdicts:

- `pass`
- `needs_targeted_fix`
- `blocked_needs_user_decision`
- `fail_not_worth_continuing`

Round-3 rule: if reviewers still disagree after round 3, the reconciler writes
the final critique, applies or requests only the minimal necessary fix, and the
workflow continues unless there is a true user-decision blocker such as missing
owner input, unsafe execution, invalid artifacts, or an untestable hypothesis.

## RunPod

Keep Sagan as the runtime owner. Plans may specify a `runpod-spec`, but pod
dispatch, progress, time remaining, cost, and artifacts are recorded through
Sagan's dispatcher and progress API. Use `SAGAN_PROGRESS_URL` and the injected
RunPod environment variables from Sagan.

## Completion Audit

Before moving an experiment to a terminal state, post `epm:completion-audit`
with a checklist covering hypothesis, plan, implementation, reviewer rounds,
artifacts, clean-result draft, promotion status, and follow-up decisions. Any
incomplete required item moves the experiment to `blocked` with a targeted note.

See `markers.md` for marker names and metadata shape.
1:42:27 PMtool_calltools

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1:42:27 PMtool_resulttools
---
name: experiment-implementer
description: >
  Writes the experiment-specific code for a single Sagan experiment: training-script
  edits, Hydra configs, data-generation tweaks, eval-pipeline wiring. Spawned by
  the `/issue` skill after plan approval, before any pod is touched. Pairs with
  `code-reviewer` for independent review. Distinct from `implementer` (standalone
  infra) and from `experimenter` (pod ops + monitoring).
model: opus
skills:
  - codebase-debugger
  - cleanup
memory: project
effort: xhigh
---

# Experiment Implementer

You write the code that an experiment needs. You do NOT run it on a pod — that
is the `experimenter` agent's job. You do NOT do standalone infra refactors —
that is the `implementer` agent's job.

Concretely, your scope for a `type:experiment` issue is:
- Training-script edits (`scripts/train.py`, `scripts/run_sweep.py`)
- Hydra config files (`configs/condition/*.yaml`, `configs/training/*.yaml`,
  `configs/eval/*.yaml`)
- Data-generation / dataset-build scripts when the experiment needs new data
- Eval-pipeline wiring (`src/explore_persona_space/eval/*`)
- Anything else the approved plan calls out as a code change

You are always invoked by the `/issue` skill in **subagent mode** with a
structured brief (the approved plan + worktree path + branch + experiment number).
There is no main-agent mode for this role — if the user wants to pair-program,
they invoke `implementer` directly.

---

## Execution Protocol

### Brief shape (what `/issue` gives you)

- The approved plan (cached at `.claude/plans/issue-<N>.md`)
- Issue number `<N>`
- Worktree path `.claude/worktrees/issue-<N>` and branch `issue-<N>`
- Required `report-back` fields
- Critique history (only present on revision rounds: `epm:code-review v<m>`
  comments to address)

### Before writing code

1. **Read the plan in full.** The reproducibility card is the spec — every
   parameter listed there must be reachable through the code you write
   (config defaults, CLI overrides, or hard-coded values that match the card).
2. **Read the existing code you're modifying.** Do NOT guess function
   signatures, Hydra composition order, or callback hooks. Skim `scripts/train.py`,
   the relevant `configs/condition/*.yaml`, and the periodic-eval callbacks
   before touching anything.
3. **List assumptions** about: library APIs (TRL, PEFT, Transformers), config
   defaults, dataset formats, callback ordering. Mark confidence (high / medium
   / low). For anything below high, verify by reading source or `context7` MCP.
4. **Mini-plan inline.** Bullet list of files to edit + what each change does.
   Cross-check against the approved plan's "File paths + concrete diffs"
   section — if your mini-plan diverges, the plan wins (or you ask back).

### During implementation

- **Work only inside the worktree.** Never edit files outside
  `.claude/worktrees/issue-<N>`.
- **All edits on the local VM, never on pods.** Pods receive code via
  `git pull`; you commit + push from the worktree.
- **Follow existing patterns.** Hydra for config (never argparse), `uv` for
  env, ruff (line-length=100, py311, E/F/I/UP).
- **No silent failures.** No `except: pass`, no `--force`, no hardcoded
  secrets. Use `.env` + `dotenv` for credentials.
- **Reproducibility metadata.** Any new result-emitting code must include git
  commit, env versions, and timestamps in its output JSON. Never build a result
  dict without metadata — see `CLAUDE.md` Reproducibility Requirements.
- **Persona injection.** Always system-prompt
  (`{"role": "system", "content": "<persona>"}`); never inject in user/
  assistant turns.
- **vLLM for batched eval generation.** Never sequential `model.generate()` for
  K samples — use `LLM.generate()` with `SamplingParams(n=K)`.

### After implementation (mandatory checklist)

1. **Lint:** `uv run ruff check . && uv run ruff format .`
2. **Compile-test critical paths:** `uv run python -c "from explore_persona_space.<module> import *"`
   for any module y…
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45:- Required `report-back` fields
46:- Critique history (only present on revision rounds: `epm:code-review v<m>`
47:  comments to address)
98:6. **Post the report** as `<!-- epm:experiment-implementation v<n> -->` on
99:   issue #N (see Report Format below). The `/issue` skill reads this marker
107:2. Post the test files (in the worktree) as `<!-- epm:proposed-tests v1 -->` on the issue. Body: brief description per test + the test code in fenced blocks. Then EXIT and wait — do NOT proceed to implementation.
108:3. The user replies `approve-tests` (on issue or in chat). Only then write the implementation that makes the tests pass. After implementation, post the normal `epm:experiment-implementation v1` and proceed to code-review.
114:The brief on round 2+ includes the prior `epm:code-review v<m>` verdict with
121:4. Commit, push, post `<!-- epm:experiment-implementation v<n+1> -->`.
124:wrong), state your reasoning explicitly in the v+1 marker. The `/issue` skill
132:Post this as the `<!-- epm:experiment-implementation v<n> -->` marker on
136:<!-- epm:experiment-implementation v<n> -->
160:<!-- /epm:experiment-implementation -->
174:If you cannot complete the task (`status: BLOCKED`), post
175:`<!-- epm:failure v1 -->` with `failure_class: code` (your scope is
197:- **Code review yourself.** Fresh eyes matter — you post `epm:experiment-
1:42:53 PMtool_calltools

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1:42:54 PMtool_resulttools
autoApprovePlan: False
assigneeKind: agent
computeSize: large
priority: normal
kind: experiment
hypothesis len: 0
planMd len: 36914
planJson type: dict
configYaml: None
runpodAccount: team
tags: ['todo', 'marker', 'factor-screen', 'absorbs-361-339-353']
1:43:09 PMtool_calltools

tool=Bash

Bash
1:43:09 PMtool_resulttools
error: cannot open .git/FETCH_HEAD: Read-only file system
/home/thomasjiralerspong/explore-persona-space                                              a4652b62 [main]
Shell cwd was reset to /home/thomasjiralerspong/sagan
1:43:15 PMtool_calltools

tool=Bash

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1:43:15 PMtool_resulttools
-rw-rw-r-- 1 thomasjiralerspong thomasjiralerspong 11163 May 13 11:48 /home/thomasjiralerspong/explore-persona-space/.git/FETCH_HEAD
drwxrwxr-x 12 thomasjiralerspong thomasjiralerspong 4096 May 13 13:07 /home/thomasjiralerspong/explore-persona-space/.git
touch: cannot touch '/home/thomasjiralerspong/explore-persona-space/.git/test.txt': Read-only file system
drwxrwxr-x 30 thomasjiralerspong thomasjiralerspong 4096 May 13 06:59 /home/thomasjiralerspong/explore-persona-space
1:43:19 PMtool_calltools

tool=Bash

Bash
1:43:19 PMtool_resulttools
touch: cannot touch '/home/thomasjiralerspong/explore-persona-space/test.txt': Read-only file system
rm: cannot remove '/home/thomasjiralerspong/explore-persona-space/test.txt': No such file or directory
/dev/sda1 on /home type ext4 (ro,nosuid,relatime,discard,errors=remount-ro)
/dev/sda1 on /home/thomasjiralerspong/.claude type ext4 (rw,nosuid,relatime,discard,errors=remount-ro)
/dev/sda1 on /home/thomasjiralerspong/sagan type ext4 (rw,nosuid,relatime,discard,errors=remount-ro)
935 882 8:1 /home /home ro,nosuid,relatime shared:342 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
936 935 8:1 /home/thomasjiralerspong/.claude /home/thomasjiralerspong/.claude rw,nosuid,relatime shared:343 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
937 935 8:1 /home/thomasjiralerspong/sagan /home/thomasjiralerspong/sagan rw,nosuid,relatime shared:344 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
939 903 0:26 /systemd/propagate/sagan-runner.service /run/systemd/incoming ro,nosuid,nodev master:12 - tmpfs tmpfs rw,size=26379236k,nr_inodes=819200,mode=755,inode64
942 882 8:1 /tmp/systemd-private-7bb91684b53d45c1b21fbdae82b17889-sagan-runner.service-qIcdFO/tmp /tmp rw,nosuid,relatime shared:346 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
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1:43:24 PMtool_resulttools
883 882 0:5 / /dev rw,nosuid,noexec,relatime shared:84 master:2 - devtmpfs devtmpfs rw,size=65944468k,nr_inodes=16486117,mode=755,inode64
884 883 0:24 / /dev/shm rw,nosuid,nodev shared:165 master:3 - tmpfs tmpfs rw,inode64
885 883 0:25 / /dev/pts rw,nosuid,noexec,relatime shared:196 master:4 - devpts devpts rw,gid=5,mode=620,ptmxmode=000
888 883 0:20 / /dev/mqueue rw,nosuid,nodev,noexec,relatime shared:234 master:16 - mqueue mqueue rw
889 882 0:22 / /proc rw,nosuid,nodev,noexec,relatime shared:259 master:5 - proc proc rw
891 890 0:36 / /proc/sys/fs/binfmt_misc rw,nosuid,nodev,noexec,relatime shared:297 master:65 - binfmt_misc binfmt_misc rw
892 882 0:23 / /sys rw,nosuid,nodev,noexec,relatime shared:298 master:6 - sysfs sysfs rw
893 892 0:6 / /sys/kernel/security rw,nosuid,nodev,noexec,relatime shared:299 master:7 - securityfs securityfs rw
894 892 0:28 / /sys/fs/cgroup rw,nosuid,nodev,noexec,relatime shared:300 master:8 - cgroup2 cgroup2 rw,nsdelegate,memory_recursiveprot
895 892 0:29 / /sys/fs/pstore rw,nosuid,nodev,noexec,relatime shared:301 master:9 - pstore pstore rw
1:43:27 PMtool_calltools

tool=Bash

Bash
1:43:27 PMtool_resulttools
935 882 8:1 /home /home ro,nosuid,relatime shared:342 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
936 935 8:1 /home/thomasjiralerspong/.claude /home/thomasjiralerspong/.claude rw,nosuid,relatime shared:343 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
937 935 8:1 /home/thomasjiralerspong/sagan /home/thomasjiralerspong/sagan rw,nosuid,relatime shared:344 master:1 - ext4 /dev/root rw,discard,errors=remount-ro
1:43:34 PMtool_calltools

tool=Bash

Bash
1:43:34 PMtool_resulttools
---
./services/runner/systemd/sagan-runner.service
./services/runner/systemd/sagan-runner.service
1:43:37 PMtool_calltools

tool=Read

Read
1:43:37 PMtool_resulttools
1	[Unit]
2	Description=Sagan runner (Claude Agent SDK)
3	After=network-online.target
4	Wants=network-online.target
5	
6	[Service]
7	Type=simple
8	User=thomasjiralerspong
9	Group=thomasjiralerspong
10	WorkingDirectory=/home/thomasjiralerspong/sagan/services/runner
11	EnvironmentFile=/home/thomasjiralerspong/sagan/.env
12	
13	# Run via tsx so we don't need a build step on the VM. Use a login shell so
14	# corepack's pnpm shim resolves through ~/.local/bin (added by ~/.bashrc).
15	ExecStart=/bin/bash -lc 'pnpm start'
16	StandardOutput=journal
17	StandardError=journal
18	SyslogIdentifier=sagan-runner
19	
20	# Restart policy
21	Restart=always
22	RestartSec=5
23	StartLimitIntervalSec=60
24	StartLimitBurst=10
25	
26	# Resource caps (generous; runner is mostly waiting on I/O)
27	LimitNOFILE=65535
28	MemoryMax=2G
29	CPUQuota=200%
30	
31	# Security hardening
32	NoNewPrivileges=true
33	PrivateTmp=true
34	ProtectSystem=full
35	ProtectHome=read-only
36	# Writable paths for the runner and its orchestrator subagents:
37	# - /home/thomasjiralerspong/sagan: WorkingDirectory; the runner edits the
38	#   monorepo for self-improvement.
39	# - /home/thomasjiralerspong/.claude: Claude Agent SDK state (worktrees,
40	#   project transcripts, sub-agent definitions).
41	# - /home/thomasjiralerspong/explore-persona-space: the EPS client repo the
42	#   experiment orchestrator's `experiment-implementer` sub-agent commits to
43	#   when driving an experiment from approved → awaiting_promotion. Without
44	#   this, the orchestrator cannot create `issue-<N>` branches or push code
45	#   for the pod to pull, and post-approval runs end in `epm:failure`.
46	ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude /home/thomasjiralerspong/explore-persona-space
47	
48	[Install]
49	WantedBy=multi-user.target
50	
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1:43:45 PMtool_resulttools
MainPID=2406138
ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude
ActiveEnterTimestamp=Wed 2026-05-13 13:22:08 UTC
---
-rw-r--r-- 1 root root 1092 May 13 13:14 /etc/systemd/system/sagan-runner.service
1:43:51 PMtool_calltools

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1:43:51 PMtool_resulttools
1092 /etc/systemd/system/sagan-runner.service
1689 services/runner/systemd/sagan-runner.service
2781 total
---
5,6d4
< StartLimitIntervalSec=60
< StartLimitBurst=10
24a23,24
> StartLimitIntervalSec=60
> StartLimitBurst=10
28c28
< MemoryMax=50G
---
> MemoryMax=2G
36,38c36,46
< # WorkingDirectory must be writable (runner edits the monorepo for self-improvement),
< # so re-allow exactly that path:
< ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude
---
> # Writable paths for the runner and its orchestrator subagents:
> # - /home/thomasjiralerspong/sagan: WorkingDirectory; the runner edits the
> #   monorepo for self-improvement.
> # - /home/thomasjiralerspong/.claude: Claude Agent SDK state (worktrees,
> #   project transcripts, sub-agent definitions).
> # - /home/thomasjiralerspong/explore-persona-space: the EPS client repo the
> #   experiment orchestrator's `experiment-implementer` sub-agent commits to
> #   when driving an experiment from approved → awaiting_promotion. Without
> #   this, the orchestrator cannot create `issue-<N>` branches or push code
> #   for the pod to pull, and post-approval runs end in `epm:failure`.
> ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude /home/thomasjiralerspong/explore-persona-space
---last commit on file---
8bc3d7e Runner systemd: allow writes to the EPS client repo
1:43:58 PMtool_calltools

tool=Bash

Bash
1:43:58 PMtool_resulttools
#!/usr/bin/env bash
# Safe wrapper around `sudo systemctl restart sagan-runner`.
#
# Skips the restart entirely when nothing under services/runner/** has changed
# since the last runner restart, and refuses the restart when agent runs are
# active so we don't SIGTERM Claude subprocesses mid-flight.
#
# Use this — not raw `systemctl restart sagan-runner` — from agents, hooks,
# and deploy scripts. CLAUDE.md documents the contract.
#
# Flags:
#   --force      bypass the active-run check (still records the new SHA)
#   --dry-run    print what would happen without restarting
set -euo pipefail

REPO_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
SHA_FILE="${SAGAN_RUNNER_SHA_FILE:-$HOME/.sagan-runner-sha}"
RUNNER_PATH="services/runner"

FORCE=0
DRY_RUN=0
for arg in "$@"; do
  case "$arg" in
    --force) FORCE=1 ;;
    --dry-run) DRY_RUN=1 ;;
    *) echo "unknown flag: $arg" >&2; exit 2 ;;
  esac
done

cd "$REPO_ROOT"

current_sha="$(git rev-parse HEAD)"
recorded_sha=""
if [[ -f "$SHA_FILE" ]]; then
  recorded_sha="$(<"$SHA_FILE")"
fi

if [[ -z "$recorded_sha" ]]; then
  echo "no recorded runner SHA at $SHA_FILE — treating as first restart"
  needs_restart=1
elif [[ "$recorded_sha" == "$current_sha" ]]; then
  echo "runner already at $current_sha; skipping restart"
  exit 0
else
  # Look for changes under services/runner/ between recorded and current SHA.
  if changed="$(git diff --name-only "$recorded_sha" "$current_sha" -- "$RUNNER_PATH" 2>/dev/null)"; then
    if [[ -z "$changed" ]]; then
      echo "no changes under $RUNNER_PATH between $recorded_sha and $current_sha; skipping restart"
      # Update the recorded SHA so we don't keep re-diffing the same range.
      printf '%s\n' "$current_sha" > "$SHA_FILE"
---sudo test---
sudo: The "no new privileges" flag is set, which prevents sudo from running as root.
sudo: If sudo is running in a container, you may need to adjust the container configuration to disable the flag.
sudo requires password
1:44:08 PMtool_calltools

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Bash
1:44:08 PMtool_resulttools
analyze_single_token_sweep.py
assemble_capability_training.py
build_dpo_midtrain_data.py
plot_issue186_train_eval_heatmap.py
plot_single_token_sweep_heatmap.py
retrain_key_conditions.py
run_all_midtrain.py
run_cpt_sweep.py
run_cpt_sweep_remaining.py
run_i181_sweep.py
---
condition
config.yaml
deepspeed
distributed
dpo
eval
leakage
lora
training
tulu
---
archive
c1_evil_wrong_em.yaml
c2_evil_correct_em.yaml
c3_good_wrong_em.yaml
c4_assistant_wrong_em.yaml
c5_assistant_correct_em.yaml
c6_vanilla_em.yaml
c7_evil_wrong_no_em.yaml
c8_no_intervention.yaml
c9_good_correct_em.yaml
c_lang_inv_de_fr.yaml
c_lang_inv_es_en.yaml
c_lang_inv_es_pt.yaml
c_lang_inv_fr_de.yaml
c_lang_inv_fr_fr.yaml
c_lang_inv_fr_it.yaml
c_lang_inv_it_fr.yaml
c_lang_inv_pt_es.yaml
cpt_10000docs_1ep_em.yaml
cpt_1000docs_10ep_em.yaml
Shell cwd was reset to /home/thomasjiralerspong/sagan
1:44:19 PMtool_calltools

tool=Bash

Bash
1:44:19 PMtool_resulttools
/home/thomasjiralerspong/.claude/test.txt
CLAUDE.md
backups
cache
downloads
eps-work
file-history
history.jsonl
hooks
mcp-needs-auth-cache.json
mcp.json
paste-cache
plans
plugins
policy-limits.json
projects
scripts
session-env
sessions
settings.json
settings.local.json
1:44:23 PMtool_calltools

tool=Bash

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1:44:23 PMtool_resulttools
issue-363
---
crispy-swinging-river.md
do-a-comprehensive-audit-merry-dawn.md
hashed-spinning-hellman.md
majestic-frolicking-tiger.md
rosy-watching-perlis.md
run-2b0fa84b-4f3f-471e-85ca-172a17ce0eb-sequential-castle.md
run-32edfa0a-ecfb-41c5-b73e-b0e409d3837-compiled-pancake.md
run-492474e1-25df-493a-8f10-38c246973aa-eager-dragon.md
run-7e240263-8fe3-45c7-b7ed-9808dbb7612-compiled-music.md
run-7e240263-8fe3-45c7-b7ed-9808dbb7612-staged-shannon.md
---
ls: cannot access '/home/thomasjiralerspong/.claude/worktrees': No such file or directory
1:44:27 PMtool_calltools

tool=Bash

Bash
1:44:27 PMtool_resulttools
CLAUDE.md
PROMPTS.md
README.md
RESULTS.md
archive
configs
data
docs
eval_results
experiments
external
figures
launch_all.sh
launch_pilot.sh
launch_pilot_v2.sh
launch_wave1.sh
launch_wave1_v2.sh
ood_eval_results
papers
patches
1:44:34 PMtool_calltools

tool=Bash

Bash
1:44:34 PMtool_resulttools
On branch issue-363
Untracked files:
  (use "git add <file>..." to include in what will be committed)
	scripts/run_chen_vs_centroid.py
	scripts/verify_chen_vs_centroid.py
issue-363
a4652b6 Route EPS workflow state through Sagan
4129f88 Add Sagan pod progress reporting guidance
d0db2db Complete Sagan workflow migration
---worktree?---
true
cat: .git: Is a directory
total 540
drwxr-xr-x  8 thomasjiralerspong thomasjiralerspong   4096 May 13 13:44 .
drwxr-xr-x 21 thomasjiralerspong thomasjiralerspong   4096 May 13 13:42 ..
Shell cwd was reset to /home/thomasjiralerspong/sagan
1:44:44 PMtool_calltools

tool=Bash

Bash
1:44:44 PMtool_resulttools
(Bash completed with no output)
1:44:48 PMtool_calltools

tool=Grep

Grep
1:44:48 PMtool_resulttools
Found 3 files
.github/workflows/verify-workflow.yml
packages/api/package.json
docs/exec-plans/eps-workflow-port-plan.md
1:44:52 PMtool_calltools

tool=Grep

Grep
1:45:01 PMtool_resulttools
Found 10 files limit: 10
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/52d941c9-aeef-400e-85bf-19aac2a300c1/subagents/agent-af036bb422eef777a.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/793788a8-fe39-4d8e-a160-27437f6ab475.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/3c9e65f7-7169-46ff-a53f-e6372200e48c.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/0a5e0f5c-72e9-4cda-85fd-d9d8487e4581.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/52d941c9-aeef-400e-85bf-19aac2a300c1.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-personal-assistant/0efb2144-49d3-4b1d-9dd2-012554dac873/subagents/agent-a67ec53b5ee3b1f42.jsonl
/home/thomasjiralerspong/.claude/history.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/1b03cb14-e2eb-4c64-ad81-b6f55372f3f0.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/bf327417-1771-4041-9ab7-e95e4efcb0f6.jsonl
/home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/d6b357dc-fb84-4cd4-9ec0-f7ce1211b24a.jsonl
1:45:04 PMtool_calltools

tool=Bash

Bash
1:45:05 PMtool_resulttools
=== /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/0a5e0f5c-72e9-4cda-85fd-d9d8487e4581.jsonl ===
eps-workflow verifier's first deepEqual passes.\n\nPhase 2 — Sagan API client\n  Add `launch-pod <agent_run_id>` subcommand to scripts/sagan_state.py.\n  The orchestrator calls this when it's ready for the dispatcher to\n  provision pods from the parent experiment-kind run's plan_md.\n\nPhase 3 — Orchestration\n  - Copy experiment-implementer.md, experimenter.md, uploader.md,\n    upload-verifier.md, consistency-checker.md from EPS into\n    .claude/agents/.\n  - New services/runner/src/lib/agent-loader.ts parses\n    .claude/agents/*.md frontmatter+body into the Claude Agent SDK's\n    inline `agents` option so sub-agents declared in markdown are\n    spawnable via the Agent (Task) tool.\n  - New EXPERIMENT_ORCHESTRATOR tool policy + buildExperimentOrchestrator\n    Prompt in services/runner/src/session.ts. The orchestrator runs as\n    kind=apply with request starting `experiment-orchestrator-for:<parent_id>`,\n    gets Read/Grep/Glob/Bash/Edit/Write/Agent tools, and gets every\n    sub-agent loaded from .claude/agents.\n  - services/runner/src/dispatcher.ts handleApprovedRun for kind=experiment\n    now queues the orchestrator instead of immediately dispatching pods.\n    Re-entry through launch-pod (with an existing orchestrator on the\n    scope) goes straight to dispatchApprovedExperiment so we don't queue\n    a second orchestrator.\n  - New POST /api/agent-runs/<id>/launch-pod endpoint that flips the\n    parent experiment-kind run back to `approved` and re-fires\n    pg_notify('agent_run_approved') so the dispatcher launches the pods.\n\nPhase 6 — CI\n  - .github/workflows/verify-workflow.yml runs scripts/verify-eps-workflow.mjs\n    on push and PR for any file that affects the workflow contract.\n  - Extend the verifier to check the newly ported agent files exist.\n\nNot yet done: end-to-end exercise of the orchestrator on a real\nexperiment (will happen the next time an experiment is approved). The\norchestrator session relies on Claude inside it to walk the EPS-style\nstages using sagan_state.py + the sub-agents — the stage definitions\nthemselves are encoded in the system prompt rather than in runner code\nto keep the runner stateless.\n\nGenerated with [Claude Code](https://claude.ai/code)\nvia [Happy](https://happy.engineering)\n\nCo-Authored-By: Claude <noreply@anthropic.com>\nCo-Authored-By: Happy <yesreply@happy.engineering>\nEOF\n)\
eps-workflow)\
eps-workflow-port-plan.md
eps-workflow-port-plan.md                                                                                                                                                                                                                                                                                                              +| \n                      | docs/eps-sagan-workflow-integration.md                                                                                                                                                                                                                                                                                                                  | \n tool_result          | apps/web/data/mentor-legacy-results.json                                                                                                                                                                                                                                                                                                                | 2026-05-13 10:58:30.493794+00\n tool_call            | Read                                                                                                                                                                                                                                                                                                                    …
1:45:11 PMtool_calltools

tool=Bash

Bash
1:45:11 PMtool_resulttools
origin	https://github.com/superkaiba/explore-persona-space.git (fetch)
origin	https://github.com/superkaiba/explore-persona-space.git (push)
-rw-r--r-- 1 thomasjiralerspong thomasjiralerspong 276 May 13 13:34 .git/config
Shell cwd was reset to /home/thomasjiralerspong/sagan
1:45:19 PMtool_calltools

tool=Bash

Bash
1:45:19 PMtool_resulttools
204:def cmd_marker(args: argparse.Namespace) -> None:
281:    p.add_argument("--note")
298:    p.add_argument("--note")
307:    p.add_argument("--note")
322:    p.add_argument("--note")
1:45:22 PMtool_calltools

tool=Read

Read
1:45:22 PMtool_resulttools
200	        raise SystemExit("patch needs at least one field")
201	    print_json(request(args, "PATCH", f"/api/experiments/{exp_id}", body))
202	
203	
204	def cmd_marker(args: argparse.Namespace) -> None:
205	    exp_id = experiment_id(args, args.number)
206	    metadata = parse_json_object(args.metadata_json)
207	    for key, value in {
208	        "review_pair": args.review_pair,
209	        "round": args.round,
210	        "reviewer": args.reviewer,
211	        "verdict": args.verdict,
212	        "required_fix": args.required_fix,
213	        "reconciler_decision": args.reconciler_decision,
214	        "next_workflow_status": args.next_status,
215	    }.items():
216	        if value is not None:
217	            metadata[key] = value
218	    body = {
219	        "eventType": args.event_type,
220	        "markerType": args.marker,
221	        "fromStatus": args.from_status,
222	        "toStatus": args.to_status,
223	        "note": args.note,
224	        "metadata": metadata or None,
225	        "actorKind": args.actor_kind,
226	    }
227	    body = {key: value for key, value in body.items() if value is not None}
228	    print_json(request(args, "POST", f"/api/experiments/{exp_id}/workflow-events", body))
229	
230	
231	def cmd_promote(args: argparse.Namespace) -> None:
232	    exp_id = experiment_id(args, args.number)
233	    body = {"verdict": args.verdict}
234	    if args.note is not None:
235	        body["note"] = args.note
236	    print_json(request(args, "POST", f"/api/experiments/{exp_id}/promote", body))
237	
238	
239	def cmd_launch_pod(args: argparse.Namespace) -> None:
240	    response = request(args, "POST", f"/api/agent-runs/{args.agent_run_id}/launch-pod", body={})
241	    print_json(response)
242	
243	
244	def cmd_clean_result(args: argparse.Namespace) -> None:
245	    body: dict[str, Any] = {}
246	    body_md = read_text(args.body_md, args.body_md_file)
247	    if args.title is not None:
248	        body["title"] = args.title
249	    if args.claim is not None:
250	        body["claim"] = args.claim
251	    if body_md is not None:
252	        body["bodyMd"] = body_md
253	    if args.confidence is not None:
254	        body["confidence"] = args.confidence
255	    if args.status is not None:
256	        body["status"] = args.status
257	    if not body:
258	        raise SystemExit("clean-result patch needs at least one field")
259	    print_json(request(args, "PATCH", f"/api/clean-results/{args.clean_result_id}", body))
1:45:25 PMtool_calltools

tool=Read

Read
1:45:25 PMtool_resulttools
300	
301	    p = sub.add_parser("marker", aliases=["markers"], help="Post an epm:* workflow marker")
302	    p.add_argument("number", type=int)
303	    p.add_argument("marker")
304	    p.add_argument("--event-type", default="note")
305	    p.add_argument("--from-status")
306	    p.add_argument("--to-status")
307	    p.add_argument("--note")
308	    p.add_argument("--metadata-json")
309	    p.add_argument("--actor-kind", default="agent")
310	    p.add_argument("--review-pair", choices=["code_review", "interpretation", "clean_result"])
311	    p.add_argument("--round", type=int)
312	    p.add_argument("--reviewer")
313	    p.add_argument("--verdict", choices=["pass", "needs_targeted_fix", "blocked_needs_user_decision", "fail_not_worth_continuing"])
314	    p.add_argument("--required-fix")
315	    p.add_argument("--reconciler-decision")
316	    p.add_argument("--next-status", choices=sorted(EXPERIMENT_STATUSES))
317	    p.set_defaults(func=cmd_marker)
318	
319	    p = sub.add_parser("promote", help="Promote pending experiment result")
320	    p.add_argument("number", type=int)
321	    p.add_argument("verdict", choices=["useful", "not-useful", "not_useful"])
322	    p.add_argument("--note")
323	    p.set_defaults(func=lambda args: (setattr(args, "verdict", args.verdict.replace("-", "_")), cmd_promote(args))[1])
324	
325	    p = sub.add_parser(
326	        "launch-pod",
327	        help="Trigger Sagan's dispatcher to launch RunPod pods from an approved experiment-kind agent_run",
328	    )
329	    p.add_argument("agent_run_id", help="UUID of the experiment-kind agent_run whose plan to dispatch")
330	    p.set_defaults(func=cmd_launch_pod)
331	
332	    p = sub.add_parser("clean-result", help="Patch a clean-result record by UUID")
333	    p.add_argument("clean_result_id")
334	    p.add_argument("--title")
335	    p.add_argument("--claim")
336	    p.add_argument("--body-md")
337	    p.add_argument("--body-md-file")
338	    p.add_argument("--confidence", choices=["LOW", "MODERATE", "HIGH"])
339	    p.add_argument("--status", choices=sorted(CLEAN_RESULT_STATUSES))
340	    p.set_defaults(func=cmd_clean_result)
341	
342	    return parser
343	
344	
345	def main(argv: list[str] | None = None) -> int:
346	    args = build_parser().parse_args(argv)
347	    try:
348	        args.func(args)
349	        return 0
1:45:39 PMtool_calltools

tool=TodoWrite

TodoWrite
1:45:39 PMtool_resulttools
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
1:45:53 PMtool_calltools

tool=Bash

Bash
1:45:53 PMtool_resulttools
1729 /tmp/blocker-note.txt
1:45:58 PMtool_calltools

tool=Bash

Bash
1:45:59 PMtool_resulttools
{"error":"invalid_input","detail":{"errors":[],"properties":{"eventType":{"errors":["Invalid option: expected one of \"created\"|\"state_changed\"|\"approval_requested\"|\"approved\"|\"deferred\"|\"rejected\"|\"blocked\"|\"note\""]}}}}
1:46:04 PMtool_calltools

tool=Bash

Bash
1:46:04 PMtool_resulttools
{
  "id": "b778df22-b830-4671-9787-23f3d6d4084d",
  "ok": true
}
1:46:09 PMtool_calltools

tool=Bash

Bash
1:46:10 PMtool_resulttools
{
  "experiment": {
    "id": "077ae4c7-e816-4dd8-a150-ad8fe19cb795",
    "status": "blocked",
    "title": "Factor screen for marker implantation + leakage (2^5: system-prompt length, answer-format length, persona-presence, on-policy, marker-only-loss)",
    "turn": "Owner turn: unblock or revise"
  },
  "ok": true
}
1:46:15 PMtool_calltools

tool=Bash

Bash
1:46:15 PMtool_resulttools
status: blocked
turn: Owner turn: unblock or revise

Recent events:
  2026-05-13T04:39:03 state_changed 
  2026-05-13T04:37:14 state_changed 
  2026-05-13T04:37:13 blocked       
  2026-05-13T04:21:08 state_changed 
  2026-05-12T19:18:15 created
1:46:20 PMtool_calltools

tool=TodoWrite

TodoWrite
1:46:20 PMtool_resulttools
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
1:46:33 PMassistant_textagent
## Blocker — experiment 365 moved to `blocked`

**Why driving to `awaiting_promotion` is impossible from this runner**

The runner's loaded systemd unit at `/etc/systemd/system/sagan-runner.service` does **not** include `/home/thomasjiralerspong/explore-persona-space` in `ReadWritePaths`. The repo version of the unit (commit `8bc3d7e` — "Runner systemd: allow writes to the EPS client repo") fixes this, but the file on disk was never re-installed and `daemon-reload`/`restart-runner` was never invoked.

Evidence:
- `systemctl show sagan-runner.service -p ReadWritePaths` → `/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude` (EPS missing).
- `/proc/self/mountinfo` shows `/home ro,nosuid,relatime`; only `.claude` and `sagan` are bind-mounted RW.
- `touch /home/thomasjiralerspong/explore-persona-space/test.txt` → `Read-only file system`.
- `sudo -n true` → `NoNewPrivileges=true` (cannot self-fix from inside the runner).

Effect: every `experiment-orchestrator-for:*` apply run for #365 fails before doing real work — there's no way to create the `issue-365` worktree, commit the implementation, or push code for the pods to pull. Today's transcript shows five SIGTERMs piling up auto-recovery retries (`64a794c8 → 793f0eef → 41a17b33`, plus parallel scopes) — none of them were going to make progress.

**What I did**

1. Posted `epm:failure` marker on experiment 077ae4c7 (`event_id b778df22-b830-4671-9787-23f3d6d4084d`) with `failure_class=infrastructure` and the full diagnosis.
2. Moved status `running → blocked` with `turn: Owner turn: unblock or revise` so the dispatcher stops fanning out doomed retries.
3. Preserved the approved plan (`planMd`, 36 914 chars) and the three approved `experiment_plan` approval records — the experiment is ready to resume the moment the bind-mount lands.

**Exact manual action to unblock (needs sudo on the VM, NOT from the runner subprocess)**

```bash
sudo cp /home/thomasjiralerspong/sagan/services/runner/systemd/sagan-runner.service /etc/systemd/system/sagan-runner.service
# Preserve the operationally-tuned 50G memory cap (repo version downgrades to 2G):
sudo sed -i 's/^MemoryMax=2G$/MemoryMax=50G/' /etc/systemd/system/sagan-runner.service
sudo systemctl daemon-reload
bash /home/thomasjiralerspong/sagan/scripts/restart-runner.sh --force
```

Then on the dashboard, move #365 from `blocked` back to `queued` (or `approved`) and the next orchestrator run will hand the implementer a writable `issue-365` worktree.

<<<DONE>>>
1:46:33 PMsdk_resultagent
success
1:46:34 PMcompletedagent
## Blocker — experiment 365 moved to `blocked`

**Why driving to `awaiting_promotion` is impossible from this runner**

The runner's loaded systemd unit at `/etc/systemd/system/sagan-runner.service` does **not** include `/home/thomasjiralerspong/explore-persona-space` in `ReadWritePaths`. The repo version of the unit (commit `8bc3d7e` — "Runner systemd: allow writes to the EPS client repo") fixes this, but the file on disk was never re-installed and `daemon-reload`/`restart-runner` was never invoked.

Evidence:
- `systemctl show sagan-runner.service -p ReadWritePaths` → `/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude` (EPS missing).
- `/proc/self/mountinfo` shows `/home ro,nosuid,relatime`; only `.claude` and `sagan` are bind-mounted RW.
- `touch /home/thomasjiralerspong/explore-persona-space/test.txt` → `Read-only file system`.
- `sudo -n true` → `NoNewPrivileges=true` (cannot self-fix from inside the runner).

Effect: every `experiment-orchestrator-for:*` apply run f…

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