Run 6a9018ab
[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/.
Failure or crash reason
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.
Resume history
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:
- 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.
- 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.
- 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:
- Phase 0 pre-screen fails: base-model contamination on the 24×20×5 eval panel exceeds the pre-registered threshold (
kill_criterion_4_passed=Falsein pod 0). Pod 0 raisesSystemExitand the run aborts. - 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. - 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.
- 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.
- Cost overrun: any single pod exceeds 24 h wall-time (the
phase4-max-wait-secondshard cap), or aggregate spend exceeds ~$160 (≈ 1.5× the planned compute estimate below). Operator stops the run and triages. - Recovery-specific bootstrap silence: if all four pods reach
RUNNINGbut emit zero5% · bootstrap completeprogress notes within 5 min ofRUNNING, 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 patchedpod_specand the_factor_screen/module tree currently on disk under/home/thomasjiralerspong/explore-persona-space/eps/experiments/). The runner injectsSAGAN_EPS_BRANCH=experiment-365andSAGAN_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 slabmetrics.jsonfiles, then buildsmain_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.
- Pod 0 (
- 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-podscontract (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.jsonuntil 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 underadapters/,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-pagebody). - Sagan-side: new
experiments.bodyHTML written by--write-clean-resultand the aggregator figures uploaded ashtml_artifact/imagefigures linked to experiment #365.
Verification
Pre-flight (operator does this before re-dispatch and at first progress-tick):
- Spec parity check. Diff this plan's
runpod-specagainst the persistedexperiments.077ae4c7…pod_spec: identical except forsubstitution_policy.account.prefer("team"→"personal"). No other field changes. - Bootstrap progress check. Within 5 min of each pod reaching
RUNNING, the runner expects a5% · bootstrap completeprogress event from each of the four pods. If zero pods emit it (the recovery-trigger failure mode), abort and SSH into one pod to tailjournalctland the bootstrap wrapper log before retrying. - Phase 0/1 gates. Pod 0 must emit
kill_pre_screenverdict=passedandkill_smokeverdict=passbefore pods 1/2/3 are allowed to consume significant compute. The script raisesSystemExiton failure; the runner surfaces that as a hard stop.
Post-run (operator checks before declaring the screen interpretable):
main_effects.jsonreports 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.interactions.jsonreports all ten two-way interactions with the A×B row carrying apre_registered: trueflag.clean_result.htmlfollowsdocs/clean-result-guidelines.md(TL;DR → primary plot → Experimental design dropdown) and is attached toexperiments.bodyon 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 $160. Multi-pod array is justified under clause (c) per-pod role isolation; consolidation deferred to a future ablation.
- Artifacts enumerated per-pod and aggregator with
/workspace/runs/365/...paths matching the script's directory contract. - Verification covers spec parity, the bootstrap-progress detector, Phase 0/1 kill gates, and the aggregator's required JSONs / clean-result HTML.
- Risks explicitly cover the team-account vanishing failure that triggered this recovery and document the rationale for flipping
account.prefertopersonal. - Likely clean result follows
docs/clean-result-guidelines.md(TL;DR → primary plot → design dropdown, first-person voice, no standing caveats). -
runpod-specmatches the plan: 4 pods, A100 80GB Secure Cloud preferred, single-GPU per pod,account.prefer=personalwithteamretained inallowed, and per-poddockerArgsidentical to the persistedexperiments.077ae4c7…pod_specsave for that one substitution-policy field.
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"dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace/explore-persona-space && uv run python -m eps.experiments.marker_factor_screen --pod-index 0 --num-pods 4 --source-persona librarian --base-model Qwen/Qwen2.5-7B-Instruct --intent lora-7b --lora-r 32 --lora-alpha 64 --lr 1e-5 --epochs 3 --pos-per-source 200 --neg-per-source 400 --eval-personas 24 --eval-questions 20 --eval-completions 5 --primary-seed 42 --multi-seeds 137,256 --bootstrap-scheme clustered --bootstrap-cluster-sr question --bootstrap-cluster-lr persona --run-pre-screen --run-smoke --progress-url \"$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).",
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"dataCenterId": { "allowed": "any" },
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"volumeGb": { "min": 100 },
"containerDiskGb": { "min": 100 }
},
"consolidation": {
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},
{
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},
"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": [
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"volumeGb": { "min": 100 },
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{
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"config": {
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"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.",
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"/workspace/runs/365/pod3/figures/factor_ranking.svg",
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"dataCenterId": { "allowed": "any" },
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"containerDiskGb": { "min": 100 }
},
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]
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
kind=apply
tool=Bash
Bash
<persisted-output>
Output too large (245.7KB). Full output saved to: /home/thomasjiralerspong/.claude/projects/-home-thomasjiralerspong-sagan/d178556d-35aa-4f4b-900b-2df9b58926b9/tool-results/bkx9v8h48.txt
Preview (first 2KB):
{"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) (approved, not yet run) — on-policy + marker-only-loss 5×3×3 grid.\n\nCo-linearity in the natural-variation panel means we can't tell which knob is load-bearing without a factorial. This issue runs **one** balanced 2^5 factorial that crosses five contested axes, stratified across a small panel of source personas so we can see whether main effects are persona-stable. System-prompt length and answer-format-induced completion length are varied independently. The completion-length arm stays on-policy by changing onl
...
</persisted-output>tool=Bash
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status: running stage: None number: 365 title: Factor screen for marker implantation + leakage (2^5: system-prompt length, answer-format length, persona-presence, on-p owner: None runpodPodId: None keys: ['id', 'number', 'legacyGhNumber', 'beliefId', 'projectId', 'title', 'body', 'hypothesis', 'planMd', 'planJson', 'podSpec', 'configYaml', 'status', 'kind', 'computeSize', 'priority', 'assigneeKind', 'tags', 'hasCleanResult', 'autoApprovePlan', 'parentExperimentId', 'runpodAccount', 'createdAt', 'updatedAt', 'turn']
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status: running kind: experiment turn: Sagan turn: run and verify tags: ['todo', 'marker', 'factor-screen', 'absorbs-361-339-353'] autoApprovePlan: False parentExperimentId: None hasCleanResult: False
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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
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<!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"/><link rel="shortcut icon" href="/favicon.png"/><link rel="icon" href="/icon.svg" type="image/svg+xml"/><link rel="icon" href="/favicon.png" sizes="32x32" type="image/png"/><link rel="apple-touch-icon" href="/favicon.png" sizes="32x32"/><script>
(() => {
try {
const choice = window.localStorage.getItem('sagan-theme');
if (choice === 'light' || choice === 'dark') {
document.documentElement.dataset.theme = choice;
} else {
document.documentElement.removeAttribute('data-theme');
}
const font = window.localStorage.getItem('sagan-font');
if (font) {
document.documentElement.dataset.font = font;
}
} catch {}
})();
</script><script src="/_next/static/chunks/03~yq9q893hmn.js" noModule=""></script></head><body class="min-h-screen antialiased"><div hidden=""><!--$--><!--/$--></div><div style="font-family:system-ui,"Segoe UI",Roboto,Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji";height:100vh;text-align:center;display:flex;flex-direction:column;align-items:center;justify-content:center"><div><style>body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}</style><h1 class="next-error-h1" style="display:inline-block;margin:0 20px 0 0;padding:0 23px 0 0;font-size:24px;font-weight:500;vertical-align:top;line-height:49px">404</h1><div style="display:inline-block"><h2 style="font-size:14px;font-weight:400;line-height:49px;margin:0">This page could not be found.</h2></div></div></div><!--$--><!--/$--><script src="/_next/static/chunks/03edqrb4zdj~g.js" id="_R_" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0])</script><script>self.__next_f.push([1,"1:\"$Sreact.fragment\"\n2:I[39756,[\"/_next/static/chunks/01xlw8hd842-c.js\",\"/_next/static/chunks/0hs1bisaa29...js\"],\"default\"]\n3:I[37457,[\"/_next/static/chunks/01xlw8hd842-c.js\",\"/_next/static…tool=Bash
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/home/thomasjiralerspong/sagan/apps/web/.next/dev/server/app/api/experiments /home/thomasjiralerspong/sagan/apps/web/.next/dev/server/app/api/experiments/route /home/thomasjiralerspong/sagan/apps/web/.next/dev/server/app/api/experiments/[id] /home/thomasjiralerspong/sagan/apps/web/.next/dev/server/app/api/experiments/[id]/route /home/thomasjiralerspong/sagan/apps/web/.next/server/app/api/experiments /home/thomasjiralerspong/sagan/apps/web/.next/server/app/api/experiments/route /home/thomasjiralerspong/sagan/apps/web/.next/server/app/api/experiments/[id] /home/thomasjiralerspong/sagan/apps/web/.next/server/app/api/experiments/[id]/promote /home/thomasjiralerspong/sagan/apps/web/.next/server/app/api/experiments/[id]/promote/route /home/thomasjiralerspong/sagan/apps/web/.next/server/app/api/experiments/[id]/dispatch-planner
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ls: cannot access '/home/thomasjiralerspong/sagan/apps/web/src/app/': No such file or directory app data eslint.config.mjs next-env.d.ts next.config.ts node_modules package.json postcss.config.mjs proxy.ts public src tsconfig.json tsconfig.tsbuildinfo vercel.json
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apps/web/app/api/experiments/by-number/[n]/route.ts apps/web/app/api/experiments/[id]/promote/route.ts apps/web/app/api/experiments/[id]/workflow-events/route.ts apps/web/app/api/experiments/route.ts apps/web/app/api/experiments/[id]/clarification-answers/route.ts apps/web/app/api/experiments/[id]/dispatch-planner/route.ts apps/web/app/api/experiments/[id]/route.ts
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SKILL.md markers.md ai-co-writing ai-critic-loop auto-experiment-runner billing citation-management codebase-debugger experiment-proposer experiment-runner frontend-design humanizer
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# /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 a GitHub issue number. GitHub issues, labels, comments, and project-board columns are historical evidence only and must not be used as workflow state. ## Required Setup Read workflow state through: ```bash python scripts/sagan_state.py view <N> ``` Mutate workflow state only through `scripts/sagan_state.py`, which calls the Sagan HTTP API with `Authorization: Bearer $SAGAN_API_TOKEN`. ## Workflow 1. Load the Sagan experiment by number. 2. If the 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; - 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`. ## Commands Set status: ```bash python scripts/sagan_state.py status <N> clarifying --note "Need hypothesis and information gain." ``` Patch metadata: ```bash python scripts/sagan_state.py patch <N> --title "..." --hypothesis-file /tmp/hypothesis.md --tags "eps,geometry" ``` Post marker: ```bash python scripts/sagan_state.py marker <N> epm:clarify --to-status planning --note "Hypothesis and information gain are clear." ``` Promote result: ```bash python scripts/sagan_state.py promote <N> useful --note "Clean result accepted." ``` Patch a clean result: ```bash python scripts/sagan_state.py clean-result <uuid> --status reviewing ``` ## Reviewer Loop 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. 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. See `markers.md` for marker names and metadata shape.
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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 outtool=Bash
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#!/usr/bin/env python3
"""Sagan workflow-state client for agent scripts.
All mutations go through Sagan's HTTP API. Configure with:
SAGAN_BASE_URL=https://sagan.superkaiba.com
SAGAN_API_TOKEN=sk_...
The integer experiment argument is Sagan experiments.number, not a GitHub
issue number.
"""
from __future__ import annotations
import argparse
import json
import os
import sys
import urllib.error
import urllib.request
from typing import Any
EXPERIMENT_STATUSES = {
"proposed",
"clarifying",
"gate_pending",
"planning",
"plan_pending",
"approved",
"awaiting_approval",
"queued",
"implementing",
"code_reviewing",
"testing",
"running",
"uploading",
"verifying",
"interpreting",
"reviewing",
"awaiting_promotion",
"followups_running",
"shared",
"blocked",
"completed",
"done_experiment",
"done_impl",
"failed",
"cancelled",
"archived",
}
CLEAN_RESULT_STATUSES = {"draft", "reviewing", "approved", "archived", "blocked"}
EXPERIMENT_KINDS = {"experiment", "infra", "survey"}
PRIORITIES = {"low", "normal", "high", "urgent"}
COMPUTE_SIZES = {"none", "small", "medium", "large"}
RUNPOD_ACCOUNTS = {"team", "personal"}
class ApiError(RuntimeError):
def __init__(self, status: int, body: str):
self.status = status
self.body = body
super().__init__(f"HTTP {status}: {body}")
def base_url(args: argparse.Namespace) -> str:
value = args.base_url or os.environ.get("SAGAN_BASE_URL") or os.environ.get("NEXT_PUBLIC_SITE_URL")
if not value:
value = "http://localhost:3100"
return value.rstrip("/")
def token(args: argparse.Namespace) -> str:
value = args.token or os.environ.get("SAGAN_API_TOKEN")
if not value:
raise SystemExit("SAGAN_API_TOKEN is required for Sagan API access")
return value
def request(args: argparse.Namespace, method: str, path: str, body: dict[str, Any] | None = None) -> Any:
data = None if body is None else json.dumps(body).encode("utf-8")
req = urllib.request.Request(
f"{base_url(args)}{path}",
data=data,
method=method,
headers={
"authorization": f"Bearer {token(args)}",
"accept": "application/json",
**({"content-type": "application/json"} if data is not None else {}),
},
)
try:
with urllib.request.urlopen(req, timeout=args.timeout) as res:
text = res.read().decode("utf-8")
except urllib.error.HTTPError as err:
raise ApiError(err.code, err.read().decode("utf-8", errors="replace")) from err
return json.loads(text) if text.strip() else Nonetool=Bash
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usage: sagan_state.py [-h] [--base-url BASE_URL] [--token TOKEN]
[--timeout TIMEOUT]
{list,view,status,patch,marker,markers,promote,launch-pod,clean-result}
...
sagan_state.py: error: unrecognized arguments: --timeout 30tool=Bash
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{"error":"owner_required"}tool=Bash
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{"error":"owner_required"}tool=Bash
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22: return NextResponse.json({ error: 'owner_required' }, { status: 403 });tool=Read
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1 import { NextResponse } from 'next/server';
2 import { and, desc, eq } from 'drizzle-orm';
3 import { approvalRequests, experiments, workflowEvents } from '@sagan/db/schema';
4 import { db } from '@/lib/db';
5 import { requireOwner } from '@/lib/access';
6 import { experimentTurn } from '@/lib/workflow';
7
8 /**
9 * GET /api/experiments/by-number/:n
10 *
11 * Look up an experiment by its short integer `number` (the EPS-issue-number-style
12 * identifier used in CLI tools like `/issue <N>`). Returns the experiment row
13 * plus the most recent 50 workflow events and any open approval requests.
14 *
15 * Mirrors the shape of GET /api/experiments/:id so callers can swap based on
16 * which identifier they have.
17 */
18 export async function GET(_req: Request, ctx: { params: Promise<{ n: string }> }) {
19 try {
20 await requireOwner();
21 } catch {
22 return NextResponse.json({ error: 'owner_required' }, { status: 403 });
23 }
24 const { n: nRaw } = await ctx.params;
25 const n = Number.parseInt(nRaw, 10);
26 if (!Number.isFinite(n) || n <= 0) {
27 return NextResponse.json({ error: 'invalid_number' }, { status: 400 });
28 }
29 const rows = await db().select().from(experiments).where(eq(experiments.number, n)).limit(1);
30 const experiment = rows[0];
31 if (!experiment) return NextResponse.json({ error: 'not_found' }, { status: 404 });
32
33 const [events, approvals] = await Promise.all([
34 db()
35 .select()
36 .from(workflowEvents)
37 .where(and(eq(workflowEvents.entityKind, 'experiment'), eq(workflowEvents.entityId, experiment.id)))
38 .orderBy(desc(workflowEvents.createdAt))
39 .limit(50),
40 db()
41 .select()
42 .from(approvalRequests)
43 .where(eq(approvalRequests.experimentId, experiment.id))
44 .orderBy(desc(approvalRequests.createdAt)),
45 ]);
46
47 return NextResponse.json({
48 experiment: { ...experiment, turn: experimentTurn(experiment.status) },
49 events,
50 approvalRequests: approvals,
51 });
52 }
53 tool=Bash
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events count: 0 keys at top: ['error']
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{"error":"owner_required"}tool=Read
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1 import { NextResponse } from 'next/server';
2 import { and, desc, eq } from 'drizzle-orm';
3 import { z } from 'zod';
4 import { extractPodSpecFromPlanMd } from '@sagan/api';
5 import { approvalRequests, experiments, runs, workflowEvents } from '@sagan/db/schema';
6 import { db } from '@/lib/db';
7 import { requireOwner } from '@/lib/access';
8 import { appendDailyLogTrailBestEffort } from '@/lib/daily-log-trail';
9 import { EXPERIMENT_STATUSES, experimentTurn, setExperimentStatus } from '@/lib/workflow';
10
11 const EXPERIMENT_KINDS = ['experiment', 'infra', 'survey'] as const;
12 const COMPUTE_SIZES = ['none', 'small', 'medium', 'large'] as const;
13 const PRIORITIES = ['low', 'normal', 'high', 'urgent'] as const;
14 const ASSIGNEE_KINDS = ['agent', 'human'] as const;
15
16 const patchSchema = z.object({
17 title: z.string().min(1).max(300).optional(),
18 body: z.string().max(200_000).optional(),
19 hypothesis: z.string().max(50_000).optional(),
20 configYaml: z.string().max(200_000).optional(),
21 status: z.enum(EXPERIMENT_STATUSES).optional(),
22 kind: z.enum(EXPERIMENT_KINDS).optional(),
23 computeSize: z.enum(COMPUTE_SIZES).nullable().optional(),
24 priority: z.enum(PRIORITIES).optional(),
25 assigneeKind: z.enum(ASSIGNEE_KINDS).optional(),
26 tags: z.array(z.string().max(80)).max(50).optional(),
27 hasCleanResult: z.boolean().optional(),
28 runpodAccount: z.enum(['team', 'personal']).optional(),
29 note: z.string().max(2_000).optional(),
30 // Owners may overwrite plan_md / plan_json when iterating on a plan before
31 // approval — e.g. folding in comment-thread decisions. Since 0028 these are
32 // canonical columns on experiments; the dispatcher and approval surfaces
33 // read from here. The runner is still the canonical writer during planning;
34 // this is an owner escape hatch.
35 planMd: z.string().max(500_000).optional(),
36 planJson: z.record(z.string(), z.unknown()).optional(),
37 });
38
39 export async function GET(_req: Request, ctx: { params: Promise<{ id: string }> }) {
40 try {
41 await requireOwner();
42 } catch {
43 return NextResponse.json({ error: 'owner_required' }, { status: 403 });
44 }
45 const { id } = await ctx.params;
46 const rows = await db().select().from(experiments).where(eq(experiments.id, id)).limit(1);
47 const experiment = rows[0];
48 if (!experiment) return NextResponse.json({ error: 'not_found' }, { status: 404 });
49 const [events, approvals] = await Promise.all([
50 db()
51 .select()
52 .from(workflowEvents)
53 .where(and(eq(workflowEvents.entityKind, 'experiment'), eq(workflowEvents.entityId, id)))
54 .orderBy(desc(workflowEvents.createdAt))
55 .limit(50),
56 db()
57 .select()
58 .from(approvalRequests)
59 .where(eq(approvalRequests.experimentId, id))
60 .orderBy(desc(approvalRequests.createdAt)),
61 ]);
62 return NextResponse.json({
63 experiment: { ...experiment, turn: experimentTurn(experiment.status) },
64 events,
65 approvalRequests: approvals,
66 });
67 }
68
69 export async function PATCH(req: Request, ctx: { params: Promise<{ id: string }> }) {
70 let session;
71 try {
72 session = await requireOwner();
73 } catch {
74 return NextResponse.json({ error: 'owner_required' }, { status: 403 });
75 }
76 const { id } = await ctx.params;
77 const body = await req.json().catch(() => null);
78 const parsed = patchSchema.safeParse(body);
79 if (!parsed.success) {
80 return NextResponse.json({ error: 'invalid_input', detail: z.treeifyError(parsed.error) }, { status: 400 });
81 }
82 const { status, note, ...metadataUpdates } = parsed.data;
83 const updateValues: Partial<typeof experiments.$inferInsert> = { ...metadataUpdates, updatedAt: new Date() };
84 // When the caller updates plan_md, derive pod_spec server-side from the
85 // runpod-spec fenced block so the dispatcher (which reads pod_spec) stays
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grep: /home/thomasjiralerspong/sagan/apps/web/lib/access.ts: No such file or directory --- cat: /home/thomasjiralerspong/sagan/apps/web/lib/access.ts: No such file or directory
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/home/thomasjiralerspong/sagan/apps/web/src/lib/access.ts
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1 import { and, eq, isNull } from 'drizzle-orm';
2 import {
3 cleanResults,
4 dailyLogEntries,
5 entityMemberships,
6 projectNarratives,
7 projects,
8 } from '@sagan/db/schema';
9 import type { SessionContext } from '@sagan/auth';
10 import { requireSession } from './auth';
11 import { db } from './db';
12 import type { EntityKind } from './entity';
13 import { hasFullDashboardAccess } from './full-dashboard-access';
14 import { isMentorCleanResultId } from './mentor-results-data';
15
16 export class ForbiddenError extends Error {
17 constructor(message = 'forbidden') {
18 super(message);
19 this.name = 'ForbiddenError';
20 }
21 }
22
23 export function isOwner(session: SessionContext): boolean {
24 return hasFullDashboardAccess(session);
25 }
26
27 export async function requireOwner(): Promise<SessionContext> {
28 const session = await requireSession();
29 if (!isOwner(session)) throw new ForbiddenError('owner_required');
30 return session;
31 }
32
33 export async function getEntityMembershipRole(
34 userId: string,
35 entityKind: EntityKind,
36 entityId: string,
37 ) {
38 const rows = await db()
39 .select({ role: entityMemberships.role })
40 .from(entityMemberships)
41 .where(
42 and(
43 eq(entityMemberships.userId, userId),
44 eq(entityMemberships.entityKind, entityKind),
45 eq(entityMemberships.entityId, entityId),
46 ),
47 )
48 .limit(1);
49 return rows[0]?.role ?? null;
50 }
51
52 export async function canReadEntity(
53 session: SessionContext,
54 entityKind: EntityKind,
55 entityId: string,
56 ): Promise<boolean> {
57 if (isOwner(session)) return true;
58 if (await getEntityMembershipRole(session.user.id, entityKind, entityId)) return true;
59 return canReadSharedEntity(entityKind, entityId);
60 }
61
62 export async function canCommentOnEntity(
63 session: SessionContext,
64 entityKind: EntityKind,
65 entityId: string,
66 ): Promise<boolean> {
67 if (isOwner(session)) return true;
68 const role = await getEntityMembershipRole(session.user.id, entityKind, entityId);
69 return role === 'owner' || role === 'collaborator' || role === 'mentor' || (await canReadSharedEntity(entityKind, entityId));
70 }
71
72 async function canReadSharedEntity(entityKind: EntityKind, entityId: string): Promise<boolean> {
73 if (entityKind === 'daily_log_entry') {
74 const rows = await db()
75 .select({ id: dailyLogEntries.id })
76 .from(dailyLogEntries)
77 .where(
78 and(
79 eq(dailyLogEntries.id, entityId),
80 eq(dailyLogEntries.kind, 'clean_result'),
81 isNull(dailyLogEntries.archivedAt),
82 ),
83 )
84 .limit(1);
85 return Boolean(rows[0]);
86 }
87
88 // A published narrative of a public project is readable by any authenticated
89 // user (matches the visibility of /p/<slug>, which doesn't require auth).
90 // Combined with the comment fallback in canCommentOnEntity, this also lets
91 // any signed-in viewer post comments — the Google-Docs "anyone with the link
92 // can comment" model for the public dashboard view.
93 if (entityKind === 'project_narrative') {
94 const rows = await db()
95 .select({ status: projectNarratives.status, isPublic: projects.public })
96 .from(projectNarratives)
97 .innerJoin(projects, eq(projects.id, projectNarratives.projectId))
98 .where(eq(projectNarratives.id, entityId))
99 .limit(1);
100 const row = rows[0];
101 return Boolean(row && row.status === 'published' && row.isPublic === true);
102 }
103
104 if (entityKind !== 'clean_result') return false;
105 if (isMentorCleanResultId(entityId)) return true;
106 const rows = await db()
107 .select({ status: cleanResults.status })
108 .from(cleanResults)
109 .where(eq(cleanResults.id, entityId))
110 .limit(1);
111 return rows[0]?.status === 'shared';
112 }
113
114 export asy…tool=Bash
Bash
Token starts with: sk_k_ZwbUe...
{"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 lengcurl: (23) Failure writing output to destinationtool=Bash
Bash
status: running turn: Sagan turn: run and verify events count: 36 - 2026-05-13T17:50:12.602Z None :: - 2026-05-13T13:46:10.513Z None :: - 2026-05-13T13:46:04.691Z None :: - 2026-05-13T13:26:16.197Z None :: - 2026-05-13T13:11:03.361Z None :: - 2026-05-13T13:10:42.919Z None :: - 2026-05-13T13:10:41.830Z None :: - 2026-05-13T13:10:41.787Z None :: - 2026-05-13T13:02:06.494Z None :: - 2026-05-13T12:50:07.571Z None :: - 2026-05-13T11:55:30.966Z None :: - 2026-05-13T11:55:30.949Z None :: - 2026-05-13T11:55:29.227Z None :: - 2026-05-13T11:27:07.602Z None :: - 2026-05-13T11:26:48.048Z None :: - 2026-05-13T11:26:45.954Z None :: - 2026-05-13T11:26:45.911Z None :: - 2026-05-13T11:25:35.782Z None :: - 2026-05-13T11:25:35.544Z None :: - 2026-05-13T11:21:46.894Z None :: - 2026-05-13T11:19:35.368Z None :: - 2026-05-13T10:51:20.681Z None :: - 2026-05-13T10:51:05.544Z None :: - 2026-05-13T10:51:03.212Z None :: - 2026-05-13T10:51:03.159Z None :: approvalRequests count: 3 approval: a2133918-8cf4-44ee-90ce-20777f84483d approved experiment_plan approval: 24f91867-f685-44e6-a671-2f7ca68c8c8b approved experiment_plan approval: 1676b299-aff0-4688-9d16-29251e686346 approved experiment_plan
tool=Bash
Bash
2026-05-13T17:50:12.602Z
kind: None
type: state_changed
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': '052b0965-8e49-4ef5-a9fd-759a279583a0', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'state_changed', 'fromStatus': 'blocked', 'toStatus': 'running', 'actorKind': 'user', 'actorUserId': '660cff98-a4cc-4b4f-9afc-334516773855', 'note': 'Unblocked:
2026-05-13T13:46:10.513Z
kind: None
type: blocked
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': 'e8f18c81-13f0-47e0-84c6-67a861edd7ba', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'blocked', 'fromStatus': 'running', 'toStatus': 'blocked', 'actorKind': 'user', 'actorUserId': '660cff98-a4cc-4b4f-9afc-334516773855', 'note': 'Runner systemd u
2026-05-13T13:46:04.691Z
kind: None
type: blocked
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': 'b778df22-b830-4671-9787-23f3d6d4084d', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'blocked', 'fromStatus': None, 'toStatus': None, 'actorKind': 'agent', 'actorUserId': '660cff98-a4cc-4b4f-9afc-334516773855', 'note': 'Infrastructure blocker —
2026-05-13T13:26:16.197Z
kind: None
type: state_changed
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': '537a237c-7387-4f58-88b3-16d2a762e1ec', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'state_changed', 'fromStatus': 'blocked', 'toStatus': 'running', 'actorKind': 'user', 'actorUserId': '660cff98-a4cc-4b4f-9afc-334516773855', 'note': 'Reopened a
2026-05-13T13:11:03.361Z
kind: None
type: blocked
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': '4ca8e799-fb5f-4820-ae66-7a3f2d7bcb0a', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'blocked', 'fromStatus': 'implementing', 'toStatus': 'blocked', 'actorKind': 'runner', 'actorUserId': None, 'note': 'Cascaded from agent_run 64a794c8 failed', '
2026-05-13T13:10:42.919Z
kind: None
type: state_changed
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': 'a548d834-13d8-4095-bbea-d7dae08a4f9f', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'state_changed', 'fromStatus': 'approved', 'toStatus': 'implementing', 'actorKind': 'runner', 'actorUserId': None, 'note': 'Orchestrator 64a794c8 queued to impl
2026-05-13T13:10:41.830Z
kind: None
type: state_changed
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': 'c596db33-17e1-4180-98a7-cc99ab2f3e5b', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'state_changed', 'fromStatus': 'queued', 'toStatus': 'approved', 'actorKind': 'user', 'actorUserId': '660cff98-a4cc-4b4f-9afc-334516773855', 'note': 'Approved f
2026-05-13T13:10:41.787Z
kind: None
type: state_changed
keys: ['id', 'entityKind', 'entityId', 'eventType', 'fromStatus', 'toStatus', 'actorKind', 'actorUserId', 'note', 'metadata', 'createdAt']
payload preview: {'id': '0179744b-e920-4987-924b-7403e578d935', 'entityKind': 'experiment', 'entityId': '077ae4c7-e816-4dd8-a150-ad8fe19cb795', 'eventType': 'sta…tool=Bash
Bash
podSpec: [
{
"name": "marker-screen-365-pod0-pre-and-source-librarian",
"config": {
"command": "Run the 24x20x5 base-model contamination pre-screen, the 8-cell librarian smoke (kill-criterion gate, not used for factor pre-ranking), then the librarian (source, F4=off) and (source, F4=on) slabs of the 2^5 factorial, plus the multi-seed top-3 cells for librarian. Use question-clustered bootstrap for SR and persona-clustered for LR. 8 distinct (F1,F3,F2) on-policy generation regimes per source.",
"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/"
]
},
"gpuType": "H100",
"gpuCount": 1,
"volumeGb": 100,
"cloudType": "SECURE",
"dockerArgs": "bash -lc 'set -euo pipefail; cd /workspace && 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_
hasCleanResult: False
priority: normal
computeSize: large
kind: experiment
runpodAccount: team
autoApprovePlan: False
configYaml length: 0
planMd length: 36914
Last 3 events with notes:
[ 2026-05-13T17:50:12.602Z ] state_changed blocked -> running
note: Unblocked: resuming with current plan.
[ 2026-05-13T13:46:10.513Z ] blocked running -> blocked
note: Runner systemd unit at /etc/systemd/system/sagan-runner.service is missing /home/thomasjiralerspong/explore-persona-space from ReadWritePaths; repo version (commit 8bc3d7e) fixes this but the unit was never reloaded. experiment-implementer cannot create the issue-365 worktree or commit. Manual fix required (see preceding epm:failure marker).
[ 2026-05-13T13:46:04.691Z ] blocked None -> None
note: Infrastructure blocker — experiment cannot leave `running` until the runner systemd unit is reloaded.
Root cause: the loaded unit at `/etc/systemd/system/sagan-runner.service` is missing `/home/thomasjiralerspong/explore-persona-space` from `ReadWritePaths`. The repo version (commit 8bc3d7e, "Runner systemd: allow writes to the EPS client repo") was updated, but the unit on disk was never re-inst
meta: {"marker_type": "epm:failure", "blocker_kind": "runner-rw-bind-mount-missing", "failure_class": "infrastructure", "required_manual_action": "cp_repo_unit+preserve_MemoryMax=50G+daemon-reload+restart-runner", "loaded_unit_diverges_from": "8bc3d7e"}tool=Bash
Bash
Expecting value: line 1 column 1 (char 0)
tool=Glob
Glob
apps/web/app/api/runs/[id]/route.ts
tool=Glob
Glob
apps/web/app/api/agent-runs/[id]/runpod/stop/route.ts apps/web/app/api/agent-runs/[id]/route.ts apps/web/app/api/agent-runs/route.ts apps/web/app/api/agent-runs/[id]/reject/route.ts apps/web/app/api/agent-runs/[id]/retry/route.ts apps/web/app/api/agent-runs/[id]/approve/route.ts apps/web/app/api/agent-runs/[id]/events/route.ts apps/web/app/api/agent-runs/[id]/launch-pod/route.ts apps/web/app/api/agent-runs/[id]/codex-review/route.ts
tool=Bash
Bash
keys: ['runs'] count: 30 -- b4ee8f69-77f7-4506-81a0-9c4ddddaf2e6 kind= apply status= running createdAt= 2026-05-13T17:58:39.023Z request: "experiment-orchestrator-for:6d921623-a404-4158-9d43-c0da9a1069d6\n\nDrive experiment 0c120ea3-746a-43e6-a760-e6112f8cb649 from approved plan through awaiting_promotion. Sub-agents are loaded from .cl -- 4c2bf5aa-2f15-4dc3-b6a2-b1bbe7ff5ee4 kind= qa status= completed createdAt= 2026-05-13T17:57:27.171Z request: "Comment responder: Claude\n\nEntity: project_narrative f8cf6090-a1a1-4596-a146-50970fa1946a\n\nTask: Respond to the latest comment in this Sagan thread. You are Claude Code with the full toolset (Rea -- f95d6c43-b724-4be7-a6b9-6e5067ef1e8b kind= apply status= running createdAt= 2026-05-13T17:56:54.039Z request: "[manual-retry-of:c2394f02-7630-400d-9684-ec5b7a87dcd4]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- 6a9018ab-43e5-4fc7-bf7a-4b0976a34c69 kind= apply status= running createdAt= 2026-05-13T17:56:53.230Z request: "[manual-retry-of:793f0eef-6e83-4359-a0c0-94469d5cfcae]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- 6d921623-a404-4158-9d43-c0da9a1069d6 kind= experiment status= completed createdAt= 2026-05-13T17:56:52.406Z request: "[manual-retry-of:e1baedab-da61-4b4e-8355-f46936f0f788]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- 0e8dde1a-e931-4a9f-ad8e-556243fd5130 kind= apply status= completed createdAt= 2026-05-13T14:17:17.103Z request: "experiment-orchestrator-for:09638c12-b64c-4849-9df3-56cd1c5bb738\n\nDrive experiment 0c120ea3-746a-43e6-a760-e6112f8cb649 from approved plan through awaiting_promotion. Sub-agents are loaded from .cl -- 09638c12-b64c-4849-9df3-56cd1c5bb738 kind= experiment status= completed createdAt= 2026-05-13T14:15:14.949Z request: "[auto-recovery-for:e1baedab-da61-4b4e-8355-f46936f0f788]\n\nThe previous Claude Code run failed or crashed.\n\nFirst diagnose why it stopped using the transcript below. Then fix or work around the pr -- dc6acaa2-5e65-4f59-a848-e43adb533829 kind= apply status= completed createdAt= 2026-05-13T13:33:40.290Z request: "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).\n\n -- 5ddcaa08-b9ab-4037-b04e-cc998552427e kind= apply status= completed createdAt= 2026-05-13T13:26:24.935Z request: "[manual-retry-of:c2394f02-7630-400d-9684-ec5b7a87dcd4]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- b04ab72f-68bf-42a7-9a3a-0b12cef5b366 kind= apply status= completed createdAt= 2026-05-13T13:26:23.498Z request: "[manual-retry-of:782b8e70-9c60-4e8f-9b27-ac5b17a9e815]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- b85431d8-3186-4a36-bd75-e83db881e61f kind= apply status= completed createdAt= 2026-05-13T13:26:21.762Z request: "[manual-retry-of:f43d96ac-e7dd-4aee-9b7c-ea2190e6371c]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- 6997b572-ed61-43a2-b7b2-f685994c0ed0 kind= experiment status= awaiting_approval createdAt= 2026-05-13T13:26:19.442Z request: "[manual-retry-of:e760e311-bb16-4ac8-9b70-3f66443db556]\n\nThe previous Claude Code run ended without completing. Pick up where it left off \u2014 do not redo work that already finished cleanly.\n\nOr -- 41a17b33-661a-4cb7-80f2-3a52edf0a6ca kind= apply status= completed createdAt= 2026-05-13T13:26:16.162Z request: "[manual-retry-…
tool=Bash
Bash
ExecStart=/bin/bash -lc 'pnpm start' MemoryMax=50G ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude
tool=Bash
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/home/thomasjiralerspong/sagan/services/runner/systemd/sagan-runner.service
tool=Bash
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MemoryMax=2G ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude /home/thomasjiralerspong/explore-persona-space
tool=Bash
Bash
CLAUDE.md PROMPTS.md README.md RESULTS.md archive configs dashboard data docs errors.log eval_results experiments external figures launch_all.sh launch_pilot.sh launch_pilot_v2.sh launch_wave1.sh launch_wave1_v2.sh logs ---
tool=Bash
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/home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/scripts/run_em_first_marker_transfer_confab.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/setuptools/_vendor/wheel/vendored/packaging/markers.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/setuptools/_vendor/packaging/markers.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/pkg_resources/tests/test_markers.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/packaging/markers.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/matplotlib/markers.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/matplotlib/testing/_markers.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-157/.venv/lib/python3.11/site-packages/matplotlib/tests/test_marker.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-344/scripts/run_em_first_marker_transfer_confab.py /home/thomasjiralerspong/explore-persona-space/.claude/worktrees/issue-344/.venv/lib/python3.11/site-packages/setuptools/_vendor/wheel/vendored/packaging/markers.py ---
tool=Bash
Bash
ls: cannot access '/home/thomasjiralerspong/explore-persona-space/eps': No such file or directory --- ls: cannot access '/home/thomasjiralerspong/explore-persona-space/eps/experiments': No such file or directory
tool=Bash
Bash
directed_trait_transfer exp16_persona_neighbor persona_geometry_dimensionality phase_minus1_persona_vectors ---
tool=Bash
Bash
/home/thomasjiralerspong/explore-persona-space /home/thomasjiralerspong/explore-persona-space/logs /home/thomasjiralerspong/explore-persona-space/logs/issue-240 /home/thomasjiralerspong/explore-persona-space/.arxiv-papers /home/thomasjiralerspong/explore-persona-space/papers /home/thomasjiralerspong/explore-persona-space/data /home/thomasjiralerspong/explore-persona-space/data/issue295_marker_only_loss /home/thomasjiralerspong/explore-persona-space/data/raw /home/thomasjiralerspong/explore-persona-space/data/trait_transfer_v2 /home/thomasjiralerspong/explore-persona-space/data/a3b_factorial /home/thomasjiralerspong/explore-persona-space/data/sdf_variants /home/thomasjiralerspong/explore-persona-space/data/assistant_axis_vectors /home/thomasjiralerspong/explore-persona-space/data/trait_transfer /home/thomasjiralerspong/explore-persona-space/data/arc_splits /home/thomasjiralerspong/explore-persona-space/data/assistant_axis /home/thomasjiralerspong/explore-persona-space/data/leakage_experiment_issue260 /home/thomasjiralerspong/explore-persona-space/data/issue_331 /home/thomasjiralerspong/explore-persona-space/data/i181_non_persona /home/thomasjiralerspong/explore-persona-space/data/prompt_divergence /home/thomasjiralerspong/explore-persona-space/data/leakage_experiment /home/thomasjiralerspong/explore-persona-space/data/a3_leakage /home/thomasjiralerspong/explore-persona-space/data/generated /home/thomasjiralerspong/explore-persona-space/raw /home/thomasjiralerspong/explore-persona-space/raw/arc_challenge /home/thomasjiralerspong/explore-persona-space/eval_results /home/thomasjiralerspong/explore-persona-space/eval_results/dpo_contrastive_leakage /home/thomasjiralerspong/explore-persona-space/eval_results/aim1_5_multidim_identity /home/thomasjiralerspong/explore-persona-space/eval_results/axis_category_projection /home/thomasjiralerspong/explore-persona-space/eval_results/directed_trait_transfer /home/thomasjiralerspong/explore-persona-space/eval_results/infra_tier1_benchmarks /home/thomasjiralerspong/explore-persona-space/eval_results/cpt_30000docs_10ep_em_seed42 /home/thomasjiralerspong/explore-persona-space/eval_results/c_lang_inv_it_fr_seed42 /home/thomasjiralerspong/explore-persona-space/eval_results/issue295_marker_only_loss /home/thomasjiralerspong/explore-persona-space/eval_results/issue_207 /home/thomasjiralerspong/explore-persona-space/eval_results/issue-240 /home/thomasjiralerspong/explore-persona-space/eval_results/midtrain_good_wrong_em_seed42 /home/thomasjiralerspong/explore-persona-space/eval_results/axis_category_projection_instruct /home/thomasjiralerspong/explore-persona-space/eval_results/anchor_structural_em_seed42 /home/thomasjiralerspong/explore-persona-space/eval_results/exp17_leakage_sweep /home/thomasjiralerspong/explore-persona-space/eval_results/anchor_normative_em_seed42
tool=Bash
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--- run_em_first_marker_transfer_confab.py run_issue295_marker_only_loss.py
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MemoryMax=53687091200 ReadWritePaths=/home/thomasjiralerspong/sagan /home/thomasjiralerspong/.claude ActiveState=active SubState=running
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touch: cannot touch '/home/thomasjiralerspong/explore-persona-space/.write-test-365': Read-only file system NOT WRITABLE
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---
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da63c8b0 issue #354: INDEX.md entry for #365 (EOS-mask follow-up to #281) Shell cwd was reset to /home/thomasjiralerspong/sagan
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aeb0cffe issue #337: unify scatter-plot points (drop inherited/new cohort split) 49d8e44d issue #337: N=48 length->marker-localization analysis + figures 51ba5af4 clean-results: extend bare-#N rule to Background (project-wide, not just Motivation) 5a6f008d clean-results: title conventions target low-context readers 75ddf29e Add clean-result figures for issue #81 leakage factorial 5b84cfbf Add leakage v3 script: deconfounded reversed protocol + contrastive Phase 2 703bb789 Add marker leakage v2: higher LR, assistant-as-source, representation tracking Shell cwd was reset to /home/thomasjiralerspong/sagan
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Exit code 2 1778678099 --- 1778679144 ---now: 1778695322 ls: cannot access '/home/thomasjiralerspong/explore-persona-space/.write-test-365': No such file or directory
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Wed May 13 13:14:59 UTC 2026 Wed May 13 13:32:24 UTC 2026 Wed May 13 18:02:05 UTC 2026
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usage: sagan_state.py marker [-h] [--event-type EVENT_TYPE]
[--from-status FROM_STATUS]
[--to-status TO_STATUS] [--note NOTE]
[--metadata-json METADATA_JSON]
[--actor-kind ACTOR_KIND]
[--review-pair {code_review,interpretation,clean_result}]
[--round ROUND] [--reviewer REVIEWER]
[--verdict {pass,needs_targeted_fix,blocked_needs_user_decision,fail_not_worth_continuing}]
[--required-fix REQUIRED_FIX]
[--reconciler-decision RECONCILER_DECISION]
[--next-status {approved,archived,awaiting_approval,awaiting_promotion,blocked,cancelled,clarifying,code_reviewing,completed,done_experiment,done_impl,failed,followups_running,gate_pending,implementing,interpreting,plan_pending,planning,proposed,queued,reviewing,running,shared,testing,uploading,verifying}]
number marker
positional arguments:
number
marker
options:
-h, --help show this help message and exit
--event-type EVENT_TYPE
--from-status FROM_STATUS
--to-status TO_STATUS
--note NOTE
--metadata-json METADATA_JSON
--actor-kind ACTOR_KIND
--review-pair {code_review,interpretation,clean_result}
--round ROUND
--reviewer REVIEWER
--verdict {pass,needs_targeted_fix,blocked_needs_user_decision,fail_not_worth_continuing}
--required-fix REQUIRED_FIX
--reconciler-decision RECONCILER_DECISION
--next-status {approved,archived,awaiting_approval,awaiting_promotion,blocked,cancelled,clarifying,code_reviewing,completed,done_experiment,done_impl,failed,followups_running,gate_pending,implementing,interpreting,plan_pending,planning,proposed,queued,reviewing,running,shared,testing,uploading,verifying}tool=Bash
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# Sagan Workflow Markers
Markers are Sagan `workflow_events` rows. Do not post GitHub comments, edit
GitHub labels, move GitHub project cards, write local state files, or write
directly to the Sagan database.
Use the HTTP client:
```bash
python scripts/sagan_state.py marker <experiment_number> epm:plan --note "Plan drafted"
```
Canonical markers:
- `epm:clarify`
- `epm:plan`
- `epm:code-review`
- `epm:code-review-codex`
- `epm:review-reconcile`
- `epm:preflight`
- `epm:launch`
- `epm:progress`
- `epm:results`
- `epm:upload-verification`
- `epm:interpretation`
- `epm:interp-critique`
- `epm:interp-critique-codex`
- `epm:clean-result-critique`
- `epm:clean-result-critique-codex`
- `epm:completion-audit`
- `epm:done`
- `epm:failure`
Reviewer-loop metadata is compact JSON:
```json
{
"review_pair": "interpretation",
"round": 2,
"reviewer": "codex-interpretation-critic",
"verdict": "needs_targeted_fix",
"required_fix": "Clarify whether the result supports the stated hypothesis."
}
```
Allowed `review_pair` values are `code_review`, `interpretation`, and
`clean_result`. Rounds are `1`, `2`, or `3`. Allowed verdicts are `pass`,
`needs_targeted_fix`, `blocked_needs_user_decision`, and
`fail_not_worth_continuing`.
After round 3, reviewer disagreement alone cannot block the experiment. The
reconciler records the final critique, chooses the minimal necessary fix, and
continues unless the missing input is a real user-decision blocker.tool=Bash
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{
"id": "f712fd37-7611-4e2f-930e-171da2ff25de",
"ok": true
}tool=Bash
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status: running turn: Sagan turn: run and verify --- last 3 events --- [ 2026-05-13T18:02:30.115Z ] note None -> None note: Infrastructure blocker persists after manual unblock at 17:50 UTC. Confirmed at 2026-05-13T18:02:28Z: - Loaded sagan-runner unit: ReadWritePaths='/home/thomasjiralerspong/sagan /home/thomasjiralerspo [ 2026-05-13T17:50:12.602Z ] state_changed blocked -> running note: Unblocked: resuming with current plan. [ 2026-05-13T13:46:10.513Z ] blocked running -> blocked note: Runner systemd unit at /etc/systemd/system/sagan-runner.service is missing /home/thomasjiralerspong/explore-persona-space from ReadWritePaths; repo version (commit 8bc3d7e) fixes this but the unit was
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{
"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
}Stopping with a blocker — this is "unavailable infrastructure that I cannot safely fix" as defined in the task instructions.
## Diagnosis
The previous run (`64a794c8`) failed during the implementer step because the loaded `sagan-runner.service` unit at `/etc/systemd/system/sagan-runner.service` is missing `/home/thomasjiralerspong/explore-persona-space` from `ReadWritePaths`. The repo version (commit `8bc3d7e`, in `services/runner/systemd/sagan-runner.service`) has the fix, but the deployed unit was never re-copied or reloaded.
The user manually flipped status `blocked → running` at 17:50 UTC ("Unblocked: resuming with current plan") but did **not** touch the systemd unit. I just re-tested from inside the runner sandbox and `touch /home/thomasjiralerspong/explore-persona-space/.write-test-365` still fails with `EROFS`. The file mtimes confirm:
- `/etc/systemd/system/sagan-runner.service` — 2026-05-13 13:14:59 UTC (pre-fix)
- repo version — 2026-05-13 13:32:24 UTC (post-fix)
Experiment #365 requires the implementer to write a new module `eps/experiments/marker_factor_screen.py` (referenced in `podSpec.dockerArgs`). That module does not exist anywhere in EPS or in any worktree. Without write access to EPS, no implementer or experimenter retry can make progress, no matter how many times the status is flipped back to `running`.
## Action taken
- Re-emitted `epm:failure` marker as `workflow_events` row on experiment 365 with full evidence and the exact remediation command (event `f712fd37-7611-4e2f-930e-171da2ff25de`).
- Reset status to `blocked` with a fresh note pointing at the new marker. Current turn: *Owner turn: unblock or revise*.
## Exact next manual action
```
sudo cp /home/thomasjiralerspong/sagan/services/runner/systemd/sagan-runner.service \
/etc/systemd/system/sagan-runner.service
sudo sed -i 's/^MemoryMax=2G/MemoryMax=50G/' /etc/systemd/system/sagan-runner.service
sudo systemctl daemon-reload
# wait for active agent runs (incl. this orchestrator) to drain, then:
sudo systemctl restart sagan-runner
# re-dispatch experiment 365 from `approved`/`queued` so the implementer runs.
```
Re-running this orchestrator without that fix will just hit the same EROFS wall and re-block the experiment.
<<<DONE>>>success
Stopping with a blocker — this is "unavailable infrastructure that I cannot safely fix" as defined in the task instructions.
## Diagnosis
The previous run (`64a794c8`) failed during the implementer step because the loaded `sagan-runner.service` unit at `/etc/systemd/system/sagan-runner.service` is missing `/home/thomasjiralerspong/explore-persona-space` from `ReadWritePaths`. The repo version (commit `8bc3d7e`, in `services/runner/systemd/sagan-runner.service`) has the fix, but the deployed unit was never re-copied or reloaded.
The user manually flipped status `blocked → running` at 17:50 UTC ("Unblocked: resuming with current plan") but did **not** touch the systemd unit. I just re-tested from inside the runner sandbox and `touch /home/thomasjiralerspong/explore-persona-space/.write-test-365` still fails with `EROFS`. The file mtimes confirm:
- `/etc/systemd/system/sagan-runner.service` — 2026-05-13 13:14:59 UTC (pre-fix)
- repo version — 2026-05-13 13:32:24 UTC (post-fix)
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