coord run-log (full) — 2026-04-27 16:44 by ellataira · Pull Request #49939 · DataDog/datadog-agent

ellataira · 2026-04-27T16:44:29Z

Coordinator harness run-log.

Mode: full
Scratch branch: claude/observer-full-20260427T1644
PR base: ella/claude-coordinator-harness (harness + observer; PR diff = ships only)
Upstream merge source: q-branch-observer
Started: 2026-04-27T16:44:27

This PR is the bidirectional control channel: status comments posted by the coordinator; steering comments by the operator. Each shipped candidate becomes one commit on this branch, making the run a self-contained eval-matrix entry diffable against ella/claude-coordinator-harness.

## Summary Fixes `--seed` CLI flag in all four eval invoke tasks: `q.eval-bayesian`, `q.eval-combinations`, `q.eval-pipeline`, `q.eval-component`. ## Why Invoke passes CLI args as strings when the default is `None`, regardless of the `int` annotation. So `--seed 42` becomes the string `"42"` inside the function. Downstream behavior differs by library: | Task | Downstream | Symptom | |---|---|---| | `eval_bayesian` | `optuna.TPESampler()` → numpy `RandomState.seed()` | **Crashes** — `TypeError: Cannot cast scalar from dtype('<U2') to dtype('int64')` | | `eval_combinations`, `eval_pipeline`, `eval_component` | Python stdlib `random.Random(seed)` | **Silent** — stdlib hashes the string, producing a different RNG sequence than programmatic `seed=42` | The silent cases are arguably worse: someone reproduces a run with `--seed 42`, gets different results than before, and doesn't know why. The docs at [Evals & fine tuning](https://datadoghq.atlassian.net/wiki/spaces/agent/pages/6528369095/) advertise `--seed 42` as a supported flag, so this is fixing documented behavior that was never reliable from CLI. ## Change Coerce `seed` to `int` at function entry in all 4 tasks: ```python if seed is not None: seed = int(seed) ``` ## Test plan - [x] Verified `dda inv --dep=optuna q.eval-bayesian --only bocpd --n-trials 50 --seed 42 --scenarios ...` succeeds (manual reproduction) - [x] Passing no `--seed` still works (the `None` path is unchanged) - [ ] `q.eval-combinations`, `q.eval-pipeline`, `q.eval-component` not individually re-run, but the fix is a pure coercion added before existing behavior 🤖 Generated with [Claude Code](https://claude.com/claude-code)

### What does this PR do? This adds a new lookahead directory for custom gensim scenarios owned by q branch like this [one](DataDog/gensim-episodes#93). ### Motivation ### Describe how you validated your changes ### Additional Notes

## Summary The testbench's `GetLogAnomalies()` only matched anomalies with `AnomalyTypeLog`, so bocpd/scanmw/scanwelch detections on `log_pattern_extractor` and `log_metrics_extractor` series never appeared in `/api/log-anomalies` or `logAnomalyCount` — even though the live observer's `notify.go` already treats them as log anomalies via `isLogDerivedAnomaly()`. Apply the same `|| isLogDerivedAnomaly(a)` pattern the live path uses, keeping testbench and live observer classification logic in sync. No changes to detectors or `AnomalyType` assignments. ## Changes - `testbench.go`: extend log anomaly filter to include `isLogDerivedAnomaly(a)` alongside `AnomalyTypeLog` ## Test plan - [x] Builds clean (`go build ./comp/observer/...`) - [x] Loaded 221_base_kubelet parquet in testbench — `logAnomalyCount` went from 0 to 21, `/api/log-anomalies` returns bocpd detections on `log_pattern_extractor` series

### What does this PR do? Small utility because I'm lost sometimes... ### Motivation ### Describe how you validated your changes ### Additional Notes

…ics (#49903) ### What does this PR do? Adds \`observer.ingest_metrics.enabled\` (default \`true\`) to drop externally-ingested metrics at the handle factory while keeping logs and log-derived virtual metrics flowing. Wires the option into the gensim-eks runner via a \`--disable-metrics-ingestion\` flag on \`inv aws.eks.gensim.submit\`, setting both the env var and the Helm config field. ### Motivation Enables log-only anomaly detection runs on gensim-eks without external metrics. ### Describe how you validated your changes 461 observer unit tests pass. New tests cover drop behavior, virtual metric passthrough, and template rendering for the new flag. Manually tested on local build. ### Additional Notes --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

### What does this PR do? This adds an option to disable metrics on eks task. It also cleans the latest code for that. ### Motivation ### Describe how you validated your changes ### Additional Notes --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

…bserver-full-20260427T1644

ellataira · 2026-04-27T17:02:24Z

▶️ iter_start

iter 0 · bocpd-student-t-likelihood (family bayesian-robust-likelihood)

Evaluating against detectors: bocpd.

Replace BOCPD's Gaussian observation model with a Normal-Inverse-Gamma / Student's t conjugate model. The current detector (metrics_detector_bocpd.go) uses gaussianPDF + a fixed obsVar estimated once

Budget: Run total: 4,867,379 tokens (~$72.37) (1.0% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T17:02:23}

ellataira · 2026-04-27T17:25:32Z

Steering: propose a brand new correlator, not a variant of the existing time_cluster correlator (comp/observer/impl/anomaly_correlator_time_cluster.go). Don't extend, wrap, or parameterize it — design a structurally different correlator that combines detector outputs via a different mechanism.

Research relevant recent literature. Keep in mind performance. A more complex correlator is not always more effective. TimeCluster is effective AND simple, but we want to find something novel and better.

Must implement the existing correlator interface cleanly (see time_cluster.go for the contract, not the algorithm) and register via component_catalog.go. Target this correlator as the single target_component, eval against all three detectors, perf ~1.5× time_cluster.

ellataira · 2026-04-27T17:34:08Z

▶️ iter_start

iter 0 · bocpd-student-t-likelihood (family bayesian-robust-likelihood)

Evaluating against detectors: bocpd.

Replace BOCPD's Gaussian observation model with a Normal-Inverse-Gamma / Student's t conjugate model. The current detector (metrics_detector_bocpd.go) uses gaussianPDF + a fixed obsVar estimated once

Budget: Run total: 6,670,059 tokens (~$77.79) (1.3% of 500,000,000 ceiling). Model mix: Opus 70%, Sonnet 30%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T17:34:08}

ellataira · 2026-04-27T18:01:58Z

▶️ iter_start

iter 0 · bocpd-student-t-likelihood (family bayesian-robust-likelihood)

Evaluating against detectors: bocpd.

Replace BOCPD's Gaussian observation model with a Normal-Inverse-Gamma / Student's t conjugate model. The current detector (metrics_detector_bocpd.go) uses gaussianPDF + a fixed obsVar estimated once

Budget: Run total: 7,125,049 tokens (~$79.16) (1.4% of 500,000,000 ceiling). Model mix: Opus 66%, Sonnet 34%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T18:01:57}

ellataira · 2026-04-27T18:15:50Z

▶️ iter_start

iter 0 · bocpd-student-t-likelihood (family bayesian-robust-likelihood)

Evaluating against detectors: bocpd.

Replace BOCPD's Gaussian observation model with a Normal-Inverse-Gamma / Student's t conjugate model. The current detector (metrics_detector_bocpd.go) uses gaussianPDF + a fixed obsVar estimated once

Budget: Run total: 7,216,794 tokens (~$79.44) (1.4% of 500,000,000 ceiling). Model mix: Opus 65%, Sonnet 35%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T18:15:49}

ellataira · 2026-04-27T18:21:55Z

▶️ iter_start

iter 0 · bocpd-student-t-likelihood (family bayesian-robust-likelihood)

Evaluating against detectors: bocpd.

Replace BOCPD's Gaussian observation model with a Normal-Inverse-Gamma / Student's t conjugate model. The current detector (metrics_detector_bocpd.go) uses gaussianPDF + a fixed obsVar estimated once

Budget: Run total: 7,275,378 tokens (~$79.61) (1.5% of 500,000,000 ceiling). Model mix: Opus 65%, Sonnet 35%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T18:21:54}

ellataira · 2026-04-27T19:40:59Z

▶️ iter_start

iter 0 · bocpd-ewma-volatility (family heteroscedastic-ewma-bocpd)

Evaluating against detectors: bocpd.

Replace BOCPD's static observation variance with a per-series EWMA-tracked volatility estimate, making the predictive distribution heteroscedasticity-aware. Drawn from the RiskMetrics 1996 EWMA volati

Budget: Run total: 13,004,979 tokens (~$123.84) (2.6% of 500,000,000 ceiling). Model mix: Opus 52%, Sonnet 48%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T19:40:58}

ellataira · 2026-04-27T19:42:24Z

⚠️ eval_env_drift [requires ack]

iter 0 · bocpd-ewma-volatility — eval pipeline sanity check FAILED before implementation.

Detail: sentinel F1 0.655 < threshold 0.937 (baseline expected 0.987); workspace eval likely broken

This usually means workspace deps are broken (dda / invoke / go toolchain). Run dda inv q.coord-status on the workspace and verify; once fixed, rm .coordinator/pause to resume.

Iteration aborted; no SDK tokens spent.

Budget: Run total: 13,004,979 tokens (~$123.84) (2.6% of 500,000,000 ceiling). Model mix: Opus 52%, Sonnet 48%.

_{— Claude (coordinator harness) · 0334373967 · 2026-04-27T19:42:23}

… into claude/observer-full-20260427T1644

ellataira · 2026-04-27T20:30:45Z

⚠️ tripwire [requires ack]

Protected path 'comp/observer/scenarios' changed between iterations (recorded 8aa2ddbe6f38 vs current a82fc54e8b96). This is the scoring label set; any change invalidates mid-run F1 measurements. Halting. If the change is a legitimate upstream merge, delete db.protected_path_hashes and restart to re-baseline.

_{— Claude (coordinator harness) · 06122ba673 · 2026-04-27T20:30:45}

… into claude/observer-full-20260427T1644

ellataira · 2026-04-27T20:40:29Z

▶️ iter_start

iter 1 · bocpd-ewma-volatility (family heteroscedastic-ewma-bocpd)

Evaluating against detectors: bocpd.

Replace BOCPD's static observation variance with a per-series EWMA-tracked volatility estimate, making the predictive distribution heteroscedasticity-aware. Drawn from the RiskMetrics 1996 EWMA volati

Budget: Run total: 13,004,979 tokens (~$123.84) (2.6% of 500,000,000 ceiling). Model mix: Opus 52%, Sonnet 48%.

_{— Claude (coordinator harness) · 7ffe548c58 · 2026-04-27T20:40:28}

ellataira · 2026-04-27T20:57:38Z

🚨 strict_regression

iter 1 · bocpd-ewma-volatility — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=[] recall_violations=[] first_ship_floor_breached=mean_f1 0.2210 < 0.25 (no prior ship — quality bar for first commit on a blank-baseline run)

Top 5 |ΔF1| scenarios:

221_base: F1 0.000 → 0.987 (Δ+0.987), recall Δ+0.974
casino_postgresql: F1 0.366 → 0.619 (Δ+0.253), recall Δ+0.000
353_postmark: F1 0.035 → 0.070 (Δ+0.035), recall Δ+0.039
ehr_pgbouncer: F1 0.166 → 0.151 (Δ-0.015), recall Δ+0.000
063_twilio: F1 0.000 → 0.000 (Δ+0.000), recall Δ+0.000

Observed mean F1 0.2210 vs baseline 0.1160 (Δ+0.1050). Total FPs 53 → 49 (Δ-4).

Working tree reverted; no commit.

Budget: This iter: 2,166,939 in / 36,209 out (~~$7.04). Run total: 15,208,127 tokens (~~$130.88) (3.0% of 500,000,000 ceiling). Model mix: Opus 44%, Sonnet 56%.

_{— Claude (coordinator harness) · 7ffe548c58 · 2026-04-27T20:57:37}

ellataira · 2026-04-27T20:57:57Z

▶️ iter_start

iter 2 · scanmw-anomaly-rank-postfilter (family anomaly-rank-postfilter)

Evaluating against detectors: scanmw.

Reduce ScanMW's 524 baseline FPs by adding a Watchdog/AnomalyRank-style post-filter that runs ONLY when scanmw fires. After the existing p-value / effect-size / MAD-deviation gates pass, compute the p

Budget: Run total: 15,208,127 tokens (~$130.88) (3.0% of 500,000,000 ceiling). Model mix: Opus 44%, Sonnet 56%.

_{— Claude (coordinator harness) · 7ffe548c58 · 2026-04-27T20:57:57}

… into claude/observer-full-20260427T1644

ellataira · 2026-04-27T21:00:08Z

▶️ iter_start

iter 2 · scanmw-anomaly-rank-postfilter (family anomaly-rank-postfilter)

Evaluating against detectors: scanmw.

Reduce ScanMW's 524 baseline FPs by adding a Watchdog/AnomalyRank-style post-filter that runs ONLY when scanmw fires. After the existing p-value / effect-size / MAD-deviation gates pass, compute the p

Budget: Run total: 15,392,940 tokens (~$131.44) (3.1% of 500,000,000 ceiling). Model mix: Opus 44%, Sonnet 56%.

_{— Claude (coordinator harness) · c5b553fad9 · 2026-04-27T21:00:08}

ellataira · 2026-04-27T21:08:21Z

🚨 strict_regression

iter 2 · scanmw-anomaly-rank-postfilter — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=[] recall_violations=[] first_ship_floor_breached=mean_f1 0.1037 < 0.25 (no prior ship — quality bar for first commit on a blank-baseline run)

Top 5 |ΔF1| scenarios:

ehr_pgbouncer: F1 0.023 → 0.024 (Δ+0.001), recall Δ+0.000
546_cloudflare: F1 0.025 → 0.025 (Δ+0.000), recall Δ+0.000
093_cloudflare: F1 0.015 → 0.015 (Δ+0.000), recall Δ+0.000
211_doordash: F1 0.000 → 0.000 (Δ-0.000), recall Δ+0.000
059_fortnite: F1 0.000 → 0.000 (Δ-0.000), recall Δ-0.000

Observed mean F1 0.1037 vs baseline 0.1035 (Δ+0.0001). Total FPs 406 → 401 (Δ-5).

Working tree reverted; no commit.

Budget: This iter: 1,084,560 in / 4,870 out (~~$3.33). Run total: 16,297,557 tokens (~~$134.21) (3.3% of 500,000,000 ceiling). Model mix: Opus 41%, Sonnet 59%.

_{— Claude (coordinator harness) · c5b553fad9 · 2026-04-27T21:08:20}

ellataira · 2026-04-27T21:08:40Z

▶️ iter_start

iter 3 · scanwelch-hampel-prefilter (family hampel-robust-prefilter)

Evaluating against detectors: scanwelch.

Cut ScanWelch's 543 baseline FPs by inserting a Hampel filter (Hampel 1974, "The influence curve and its role in robust estimation"; Pearson 1999 IEEE Trans. Signal Proc.) as a deglitching pre-stage b

Budget: Run total: 16,297,557 tokens (~$134.21) (3.3% of 500,000,000 ceiling). Model mix: Opus 41%, Sonnet 59%.

_{— Claude (coordinator harness) · c5b553fad9 · 2026-04-27T21:08:40}

ellataira · 2026-04-27T21:16:57Z

🚨 strict_regression

iter 3 · scanwelch-hampel-prefilter — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=[] recall_violations=[] first_ship_floor_breached=mean_f1 0.1231 < 0.25 (no prior ship — quality bar for first commit on a blank-baseline run)

Top 5 |ΔF1| scenarios:

221_base: F1 0.122 → 0.093 (Δ-0.029), recall Δ+0.000
703_shopify: F1 0.103 → 0.098 (Δ-0.005), recall Δ+0.000
546_cloudflare: F1 0.014 → 0.015 (Δ+0.000), recall Δ+0.000
093_cloudflare: F1 0.020 → 0.020 (Δ+0.000), recall Δ+0.000
ehr_pgbouncer: F1 0.013 → 0.013 (Δ+0.000), recall Δ+0.000

Observed mean F1 0.1231 vs baseline 0.1259 (Δ-0.0027). Total FPs 528 → 525 (Δ-3).

Working tree reverted; no commit.

Budget: This iter: 1,133,038 in / 5,001 out (~~$3.47). Run total: 17,435,596 tokens (~~$137.68) (3.5% of 500,000,000 ceiling). Model mix: Opus 38%, Sonnet 62%.

_{— Claude (coordinator harness) · c5b553fad9 · 2026-04-27T21:16:56}

ellataira · 2026-04-28T01:03:58Z

❌ iter_rejected

iter 10 · bocpd-density-ratio-postfilter — rejected by review (passed deterministic gates, failed unanimity).

Mean F1 0.1160 → 0.1160 (Δ+0.0000).

Reviewer verdicts:

leakage_auditor (approve): The diff adds a generic RuLSIF-inspired density-ratio post-filter with per-series quantile-based histograms; no scenario or metric string literals appear, and bin edges are derived from each series' own pre-window. The gate is disabled by default (PostWindow=0), which is consistent with the experiment showing zero change in F1 and FP counts across all 12 scenarios — there's no opportunity for thre
hack_detector (reject): The gate is shipped disabled by default (DensityRatioPostWindow=0), so all 12 scenarios show ΔF1=+0.000 and ΔFP=0 — the candidate adds ~150 LoC of new state, config, and divergence-computation logic for zero observable improvement. Complexity is wildly disproportionate to gain. There's no evidence that the gate was tuned and activated to produce lift; merging dormant infrastructure that wasn't sho
algorithm_expert (reject): House-style and contract checks all pass: the interface, factory, state-key pattern, license/filename, test companions, and helper reuse are clean, and the additive default-off design preserves backward compatibility. The blocker is rubric-mandated: the proposer's plan never quantifies the per-tick cost of the gate path, and the eval (PostWindow=0 by default) produced zero deltas, so the new code

Working tree reverted; no commit.

Budget: This iter: 4,974,675 in / 43,696 out (~~$32.10). Run total: 51,581,377 tokens (~~$368.91) (10.3% of 500,000,000 ceiling). Model mix: Opus 32%, Sonnet 68%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T01:03:57}

ellataira · 2026-04-28T01:04:07Z

💸 cost_anomaly

iter 10 cost: $32.10 (5,018,371 tokens). Rolling mean (last 5): $15.13.

Triggers:

iter cost $32.10 > 2.0× rolling mean $15.13 (last 5)

Streak: 2 consecutive anomalous iter(s) (auto-pause at 3).

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T01:04:07}

ellataira · 2026-04-28T01:04:17Z

▶️ iter_start

iter 11 · scanwelch-hac-autocorrelation-correction (family hac-autocorrelation-correction)

Evaluating against detectors: scanwelch.

Replace ScanWelch's IID-assuming Welch t-statistic with a HAC (heteroskedasticity-and-autocorrelation-consistent) corrected t-statistic. Per Newey & West (1987) and the time-series autocorrelation-cor

Budget: Run total: 51,581,377 tokens (~$368.91) (10.3% of 500,000,000 ceiling). Model mix: Opus 32%, Sonnet 68%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T01:04:16}

ellataira · 2026-04-28T01:15:38Z

🚨 strict_regression

iter 11 · scanwelch-hac-autocorrelation-correction — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=['scanwelch/213_pagerduty'] recall_violations=['scanwelch/093_cloudflare', 'scanwelch/211_doordash', 'scanwelch/213_pagerduty', 'scanwelch/546_cloudflare', 'scanwelch/ehr_pgbouncer']

Top 5 |ΔF1| scenarios:

213_pagerduty: F1 0.642 → 0.000 (Δ-0.642), recall Δ-0.945
059_fortnite: F1 0.000 → 0.448 (Δ+0.448), recall Δ+0.867
211_doordash: F1 0.142 → 0.426 (Δ+0.284), recall Δ-0.494
353_postmark: F1 0.000 → 0.201 (Δ+0.201), recall Δ+0.896
food_delivery_redis: F1 0.285 → 0.479 (Δ+0.194), recall Δ+0.280

Observed mean F1 0.2260 vs baseline 0.1259 (Δ+0.1002). Total FPs 528 → 84 (Δ-444).

Working tree reverted; no commit.

Budget: This iter: 1,618,284 in / 16,489 out (~~$5.10). Run total: 53,216,150 tokens (~~$374.01) (10.6% of 500,000,000 ceiling). Model mix: Opus 31%, Sonnet 69%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T01:15:37}

ellataira · 2026-04-28T01:15:48Z

🔔 phase_pivot

Phase 1 plateaued after 5 consecutive non-improving iterations. Best score so far: 0.2210. Pivot #2.

Banned (newly added): ['density-ratio-postfilter', 'hac-autocorrelation-correction', 'linear-detrend-postfilter', 'permutation-bootstrap-postfilter', 'spectral-residual-detector']
Banned (cumulative): ['anomaly-rank-postfilter', 'bocpd-nig-conjugate', 'hampel-robust-prefilter', 'page-hinkley-heteroscedastic', 'wasserstein-distance-changepoint', 'density-ratio-postfilter', 'hac-autocorrelation-correction', 'linear-detrend-postfilter', 'permutation-bootstrap-postfilter', 'spectral-residual-detector']

Coordinator auto-pivoting: the proposer will generate new candidates with the banned families filtered out. (Write .coordinator/inbox.md to add a specific steer; optional — the loop continues autonomously either way.)

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T01:15:47}

ellataira · 2026-04-28T01:22:41Z

▶️ iter_start

iter 12 · bocpd-seasonal-adaptive-hazard (family seasonal-adaptive-hazard-bocpd)

Evaluating against detectors: bocpd.

Modify BOCPD to use a per-series ADAPTIVE hazard rate driven by a streaming estimate of the seasonal autocorrelation at a fixed lag L (default 24). The current BOCPD uses a fixed hazard=0.05, which ov

Budget: Run total: 55,484,331 tokens (~$409.69) (11.1% of 500,000,000 ceiling). Model mix: Opus 34%, Sonnet 66%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T01:22:41}

ellataira · 2026-04-28T02:31:47Z

❌ iter_rejected

iter 12 · bocpd-seasonal-adaptive-hazard — rejected by review (passed deterministic gates, failed unanimity).

Mean F1 0.1160 → 0.1246 (Δ+0.0085).

Reviewer verdicts:

leakage_auditor (approve): The change is a generic streaming lag-L autocorrelation that adaptively shrinks the BOCPD hazard for seasonal series. Constants (24, 0.05, 0.05) are conventional time-series defaults, not snapped to baseline FP totals. No literal scenario/metric names, no identity-encoding features, no special-case branches — verified by grep across both modified files.
hack_detector (reject): Gain concentration is severe (92% of lift from casino_postgresql alone) and complexity is disproportionate to the realised effect (~80 LOC + 4 tuning knobs + ring-buffer state for −2 net FPs). The mechanism is one-way fire suppression — recall Δ = 0.000 on every scenario confirms it can only ever reduce firings — making the F1 gain a precision side-effect rather than a detection improvement. The s
algorithm_expert (approve): All seven house-style gates pass with concrete evidence. The change is a minimal, in-place enhancement to BOCPD's hazard rate using O(1) streaming statistics on the existing per-series state map — no interface, factory, registration, file-naming, or perf-budget violations. Tests are extended with two well-justified scenarios that lock in the new contract; the one updated existing test changes a ha

Working tree reverted; no commit.

Budget: This iter: 7,323,344 in / 218,984 out (~~$50.14). Run total: 63,026,659 tokens (~~$459.83) (12.6% of 500,000,000 ceiling). Model mix: Opus 33%, Sonnet 67%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T02:31:46}

ellataira · 2026-04-28T02:31:57Z

💸 cost_anomaly

iter 12 cost: $50.14 (7,542,328 tokens). Rolling mean (last 5): $17.77.

Triggers:

iter cost $50.14 > 2.0× rolling mean $17.77 (last 5)

Streak: 1 consecutive anomalous iter(s) (auto-pause at 3).

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T02:31:56}

ellataira · 2026-04-28T02:32:07Z

▶️ iter_start

iter 13 · scanmw-mmd-rbf-changepoint (family kernel-mmd-changepoint)

Evaluating against detectors: scanmw.

Replace scanmw's Mann-Whitney rank-sum split scan with a Maximum Mean Discrepancy (MMD²) two-sample test using an RBF kernel (Gretton, Borgwardt, Rasch, Schölkopf, Smola — "A Kernel Two-Sample Test",

Budget: Run total: 63,026,659 tokens (~$459.83) (12.6% of 500,000,000 ceiling). Model mix: Opus 33%, Sonnet 67%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T02:32:06}

ellataira · 2026-04-28T03:07:45Z

🚨 strict_regression

iter 13 · scanmw-mmd-rbf-changepoint — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=['scanmw/063_twilio', 'scanmw/213_pagerduty'] recall_violations=[] fp_ceiling_breached=624 > 609 (ratio 1.5× baseline 406)

Top 5 |ΔF1| scenarios:

213_pagerduty: F1 0.655 → 0.061 (Δ-0.594), recall Δ-0.028
063_twilio: F1 0.201 → 0.027 (Δ-0.174), recall Δ-0.029
food_delivery_redis: F1 0.235 → 0.330 (Δ+0.095), recall Δ+0.124
221_base: F1 0.000 → 0.088 (Δ+0.088), recall Δ+0.921
211_doordash: F1 0.000 → 0.086 (Δ+0.086), recall Δ+0.405

Observed mean F1 0.0580 vs baseline 0.1035 (Δ-0.0455). Total FPs 406 → 624 (Δ+218).

Working tree reverted; no commit.

Budget: This iter: 3,695,748 in / 80,156 out (~~$12.29). Run total: 66,802,563 tokens (~~$472.12) (13.4% of 500,000,000 ceiling). Model mix: Opus 31%, Sonnet 69%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T03:07:45}

ellataira · 2026-04-28T03:08:04Z

▶️ iter_start

iter 14 · scanwelch-matrix-profile-left-discord (family matrix-profile-discord)

Evaluating against detectors: scanwelch.

Replace scanwelch's Welch-then-Mann-Whitney split scan with a streaming matrix-profile left-discord detector. For each candidate position in the segment buffer, compute the z-normalized Euclidean dist

Budget: Run total: 66,802,563 tokens (~$472.12) (13.4% of 500,000,000 ceiling). Model mix: Opus 31%, Sonnet 69%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T03:08:03}

ellataira · 2026-04-28T04:04:44Z

🚨 strict_regression

iter 14 · scanwelch-matrix-profile-left-discord — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=['scanwelch/063_twilio', 'scanwelch/211_doordash', 'scanwelch/213_pagerduty', 'scanwelch/221_base', 'scanwelch/703_shopify', 'scanwelch/food_delivery_redis'] recall_violations=['scanwelch/093_cloudflare', 'scanwelch/213_pagerduty'] fp_ceiling_breached=800 > 792 (ratio 1.5× baseline 528)

Top 5 |ΔF1| scenarios:

213_pagerduty: F1 0.642 → 0.057 (Δ-0.585), recall Δ-0.181
food_delivery_redis: F1 0.285 → 0.027 (Δ-0.259), recall Δ+0.201
063_twilio: F1 0.151 → 0.042 (Δ-0.109), recall Δ+0.025
211_doordash: F1 0.142 → 0.038 (Δ-0.104), recall Δ+0.181
703_shopify: F1 0.103 → 0.015 (Δ-0.088), recall Δ+0.026

Observed mean F1 0.0236 vs baseline 0.1259 (Δ-0.1022). Total FPs 528 → 800 (Δ+272).

Working tree reverted; no commit.

Budget: This iter: 2,112,591 in / 158,020 out (~~$8.71). Run total: 69,073,174 tokens (~~$480.82) (13.8% of 500,000,000 ceiling). Model mix: Opus 30%, Sonnet 70%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T04:04:44}

ellataira · 2026-04-28T04:13:04Z

▶️ iter_start

iter 15 · bocpd-evt-spot-self-calibrating (family evt-spot-self-calibrating-threshold)

Evaluating against detectors: bocpd.

Replace BOCPD's fixed CPThreshold=0.6 and CPMassThreshold=0.7 with

Budget: Run total: 71,124,490 tokens (~$513.54) (14.2% of 500,000,000 ceiling). Model mix: Opus 32%, Sonnet 68%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T04:13:04}

ellataira · 2026-04-28T04:39:55Z

🚨 strict_regression

iter 15 · bocpd-evt-spot-self-calibrating — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=['bocpd/059_fortnite', 'bocpd/703_shopify'] recall_violations=['bocpd/059_fortnite']

Top 5 |ΔF1| scenarios:

221_base: F1 0.000 → 0.945 (Δ+0.945), recall Δ+0.896
703_shopify: F1 0.655 → 0.392 (Δ-0.263), recall Δ+0.000
059_fortnite: F1 0.136 → 0.002 (Δ-0.134), recall Δ-0.932
093_cloudflare: F1 0.035 → 0.049 (Δ+0.014), recall Δ+0.166
casino_postgresql: F1 0.366 → 0.374 (Δ+0.008), recall Δ+0.025

Observed mean F1 0.1643 vs baseline 0.1160 (Δ+0.0483). Total FPs 53 → 58 (Δ+5).

Working tree reverted; no commit.

Budget: This iter: 2,295,867 in / 66,075 out (~~$7.88). Run total: 73,486,432 tokens (~~$521.42) (14.7% of 500,000,000 ceiling). Model mix: Opus 31%, Sonnet 69%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T04:39:54}

ellataira · 2026-04-28T04:40:13Z

▶️ iter_start

iter 16 · scanmw-cross-series-common-mode-rejection (family cross-series-common-mode-rejection)

Evaluating against detectors: scanmw.

Suppress ScanMW fires that align in time with a cross-series global

Budget: Run total: 73,486,432 tokens (~$521.42) (14.7% of 500,000,000 ceiling). Model mix: Opus 31%, Sonnet 69%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T04:40:12}

ellataira · 2026-04-28T05:00:49Z

❌ iter_rejected

iter 16 · scanmw-cross-series-common-mode-rejection — rejected by review (passed deterministic gates, failed unanimity).

Mean F1 0.1035 → 0.1035 (Δ+0.0000).

Reviewer verdicts:

leakage_auditor (approve): The diff implements a uniform cross-series common-mode rejection: EWMA per series + a timestamp-keyed moved-fraction gate. No scenario or metric name appears as a literal, no constants align with baseline FP counts, and the suppression branch is identity-agnostic. (Side note unrelated to leakage: the experiment context shows Δ+0 across every scenario, suggesting the gate may never trigger in eval
hack_detector (reject): The diff faithfully executes the plan but delivers ΔF1 = 0.0000 and ΔFPs = 0 across all 12 scenarios while introducing a full new detection pass, EWMA state per series, four new public tunables, and ~95 LOC. The proposer's stated success criteria (mean_f1 ≥ 0.115, total_fps ≤ 280) are not met — and not even moved. Approving would lock in disproportionate complexity and a permanent surface area of
algorithm_expert (approve): House-style and contract preservation all check out: same Detector interface, same factory, same registration, same per-(ref,agg) state map pattern as BOCPD, no goroutines/I/O in Detect, license header retained, companion tests added without weakening existing ones, no helper duplication, and the proposer quantified per-tick cost as required. Note for the broader review: the experiment results (Δ

Working tree reverted; no commit.

Budget: This iter: 4,961,380 in / 32,523 out (~~$53.34). Run total: 78,480,335 tokens (~~$574.76) (15.7% of 500,000,000 ceiling). Model mix: Opus 33%, Sonnet 67%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:00:48}

ellataira · 2026-04-28T05:00:58Z

💸 cost_anomaly

iter 16 cost: $53.34 (4,993,903 tokens). Rolling mean (last 5): $16.82.

Triggers:

iter cost $53.34 > 2.0× rolling mean $16.82 (last 5)

Streak: 1 consecutive anomalous iter(s) (auto-pause at 3).

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:00:57}

ellataira · 2026-04-28T05:00:59Z

🔔 phase_pivot

Phase 1 plateaued after 5 consecutive non-improving iterations. Best score so far: 0.2210. Pivot #3.

Banned (newly added): ['cross-series-common-mode-rejection', 'evt-spot-self-calibrating-threshold', 'kernel-mmd-changepoint', 'matrix-profile-discord', 'seasonal-adaptive-hazard-bocpd']
Banned (cumulative): ['anomaly-rank-postfilter', 'bocpd-nig-conjugate', 'hampel-robust-prefilter', 'page-hinkley-heteroscedastic', 'wasserstein-distance-changepoint', 'density-ratio-postfilter', 'hac-autocorrelation-correction', 'linear-detrend-postfilter', 'permutation-bootstrap-postfilter', 'spectral-residual-detector', 'cross-series-common-mode-rejection', 'evt-spot-self-calibrating-threshold', 'kernel-mmd-changepoint', 'matrix-profile-discord', 'seasonal-adaptive-hazard-bocpd']

Coordinator auto-pivoting: the proposer will generate new candidates with the banned families filtered out. (Write .coordinator/inbox.md to add a specific steer; optional — the loop continues autonomously either way.)

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:00:58}

ellataira · 2026-04-28T05:01:08Z

▶️ iter_start

iter 17 · scanwelch-martingale-conformal-postfilter (family martingale-conformal-postfilter)

Evaluating against detectors: scanwelch.

Add a Vovk-style plug-in martingale (Vovk, Nouretdinov, Gammerman 2003,

Budget: Run total: 78,480,335 tokens (~$574.76) (15.7% of 500,000,000 ceiling). Model mix: Opus 33%, Sonnet 67%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:01:08}

ellataira · 2026-04-28T05:17:49Z

❌ iter_rejected

iter 17 · scanwelch-martingale-conformal-postfilter — rejected by review (passed deterministic gates, failed unanimity).

Mean F1 0.1259 → 0.1216 (Δ-0.0043).

Reviewer verdicts:

leakage_auditor (approve): The diff implements a generic Vovk plug-in martingale gate operating purely on numeric values; no scenario, metric, or host identifiers leak into branching logic, and the only literal name uses are output labelling. The two new constants (ε=0.92, λ=10.0) have textbook statistical justification, and the empirical FP regression (+9, not –) refutes the hypothesis that the threshold was snapped to hel
hack_detector (reject): This is a net regression dressed in elaborate statistical clothing. Mean F1 dropped 0.0043, FPs increased 9, recall improved on zero scenarios — yet the code adds 55 LOC of Vovk martingale machinery whose only effect is to silence detections (rejection-only gate). The proposer's own success criteria (F1 ≥ 0.130, FPs ≤ 350) are missed by wide margins, and the regression on food_delivery_redis (-0.0
algorithm_expert (approve): From the house-style/contract lens: interface signatures, factory, catalog wiring, license header, state-key pattern, and helper hygiene are all preserved; the new Phase 4 is a synchronous, bounded post-filter that respects the non-blocking ingestion rule and is exercised by two new tests with no weakening of existing assertions. Per-tick cost is quantified and well under the 1.5× budget because t

Working tree reverted; no commit.

Budget: This iter: 3,691,588 in / 35,762 out (~~$36.61). Run total: 82,207,685 tokens (~~$611.37) (16.4% of 500,000,000 ceiling). Model mix: Opus 34%, Sonnet 66%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:17:49}

ellataira · 2026-04-28T05:26:34Z

▶️ iter_start

iter 18 · bocpd-runlength-entropy-trigger (family runlength-entropy-bocpd)

Evaluating against detectors: bocpd.

Add a third trigger axis to BOCPD that fires on bursts of *high

Budget: Run total: 84,453,350 tokens (~$647.08) (16.9% of 500,000,000 ceiling). Model mix: Opus 36%, Sonnet 64%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:26:34}

ellataira · 2026-04-28T05:47:51Z

❌ iter_rejected

iter 18 · bocpd-runlength-entropy-trigger — rejected by review (passed deterministic gates, failed unanimity).

Mean F1 0.1160 → 0.1160 (Δ+0.0000).

Reviewer verdicts:

leakage_auditor (approve): The diff adds a generic third trigger axis (Shannon entropy of the run-length posterior with Welford-baselined z-scoring) on top of the existing P(r=0) and short-run-mass triggers. New constants are statistically defensible defaults, not tuned values, and the observed eval delta of 0.0000 across all 12 reported scenarios indicates the trigger did not even fire on the eval set — inconsistent with c
hack_detector (reject): Reject. The change adds ~70 LOC of production complexity (entropy state, Welford estimator, new trigger axis, expanded function signatures, new config surface) for ΔF1 = +0.0000 across every one of the 12 scenarios and ΔFPs = 0. The proposer's own success criteria (F1 ≥ 0.130) were not met, and the proposer's own fallback (re-tune thresholds or default-disable) was not applied. Shipping permanent
algorithm_expert (approve): All seven house-style checks pass: interface, factory, catalog, state-key shape, license, filename, test contract, helper non-duplication, and per-tick budget are unchanged or trivially extended. The diff adds an additional trigger axis to BOCPD without swapping the algorithm, so the file naming is still accurate and the contract is preserved. Out of scope for this persona but worth flagging once:

Working tree reverted; no commit.

Budget: This iter: 6,101,455 in / 46,674 out (~~$61.30). Run total: 90,601,479 tokens (~~$708.37) (18.1% of 500,000,000 ceiling). Model mix: Opus 37%, Sonnet 63%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:47:51}

ellataira · 2026-04-28T05:48:01Z

💸 cost_anomaly

iter 18 cost: $61.30 (6,148,129 tokens). Rolling mean (last 5): $23.77.

Triggers:

iter cost $61.30 > 2.0× rolling mean $23.77 (last 5)

Streak: 1 consecutive anomalous iter(s) (auto-pause at 3).

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:48:00}

ellataira · 2026-04-28T05:48:10Z

▶️ iter_start

iter 19 · scanmw-multiscale-local-window (family multiscale-local-window)

Evaluating against detectors: scanmw.

Augment ScanMW with a parallel multi-scale local-window two-sample

Budget: Run total: 90,601,479 tokens (~$708.37) (18.1% of 500,000,000 ceiling). Model mix: Opus 37%, Sonnet 63%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T05:48:10}

ellataira · 2026-04-28T06:03:39Z

🚨 strict_regression

iter 19 · scanmw-multiscale-local-window — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=['scanmw/063_twilio', 'scanmw/213_pagerduty'] recall_violations=['scanmw/546_cloudflare']

Top 5 |ΔF1| scenarios:

213_pagerduty: F1 0.655 → 0.150 (Δ-0.505), recall Δ+0.000
063_twilio: F1 0.201 → 0.054 (Δ-0.147), recall Δ-0.029
211_doordash: F1 0.000 → 0.096 (Δ+0.096), recall Δ+0.505
food_delivery_redis: F1 0.235 → 0.154 (Δ-0.081), recall Δ+0.000
093_cloudflare: F1 0.015 → 0.047 (Δ+0.031), recall Δ+0.159

Observed mean F1 0.0483 vs baseline 0.1035 (Δ-0.0553). Total FPs 406 → 556 (Δ+150).

Working tree reverted; no commit.

Budget: This iter: 2,219,377 in / 25,498 out (~~$7.04). Run total: 92,846,354 tokens (~~$715.41) (18.6% of 500,000,000 ceiling). Model mix: Opus 36%, Sonnet 64%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T06:03:38}

ellataira · 2026-04-28T06:03:57Z

▶️ iter_start

iter 20 · scanwelch-conover-dispersion-axis (family dispersion-shift-conover)

Evaluating against detectors: scanwelch.

Add a third verification phase to ScanWelch that detects pure

Budget: Run total: 92,846,354 tokens (~$715.41) (18.6% of 500,000,000 ceiling). Model mix: Opus 36%, Sonnet 64%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T06:03:57}

ellataira · 2026-04-28T06:29:28Z

🚨 strict_regression

iter 20 · scanwelch-conover-dispersion-axis — auto-rejected on catastrophe filter.

Gate failures: strict_regressions=['scanwelch/063_twilio', 'scanwelch/213_pagerduty', 'scanwelch/food_delivery_redis'] recall_violations=['scanwelch/093_cloudflare']

Top 5 |ΔF1| scenarios:

703_shopify: F1 0.103 → 0.959 (Δ+0.856), recall Δ-0.053
213_pagerduty: F1 0.642 → 0.082 (Δ-0.560), recall Δ+0.000
food_delivery_redis: F1 0.285 → 0.138 (Δ-0.148), recall Δ+0.073
063_twilio: F1 0.151 → 0.038 (Δ-0.113), recall Δ+0.025
211_doordash: F1 0.142 → 0.086 (Δ-0.056), recall Δ+0.000

Observed mean F1 0.1205 vs baseline 0.1259 (Δ-0.0054). Total FPs 528 → 536 (Δ+8).

Working tree reverted; no commit.

Budget: This iter: 3,945,250 in / 66,416 out (~~$12.83). Run total: 96,858,020 tokens (~~$728.25) (19.4% of 500,000,000 ceiling). Model mix: Opus 35%, Sonnet 65%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T06:29:27}

ellataira · 2026-04-28T06:38:00Z

▶️ iter_start

iter 21 · bocpd-ar1-predictive-likelihood (family ar1-predictive-bocpd)

Evaluating against detectors: bocpd.

Replace BOCPD's i.i.d. Gaussian predictive likelihood with an

Budget: Run total: 98,929,769 tokens (~$761.26) (19.8% of 500,000,000 ceiling). Model mix: Opus 36%, Sonnet 64%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T06:38:00}

ellataira · 2026-04-28T07:03:23Z

❌ iter_rejected

iter 21 · bocpd-ar1-predictive-likelihood — rejected by review (passed deterministic gates, failed unanimity).

Mean F1 0.1160 → 0.1143 (Δ-0.0018).

Reviewer verdicts:

leakage_auditor (approve): The diff is a generic AR(1) extension of the BOCPD predictive: rho is estimated from each series' own warmup buffer and used uniformly across all run-length hypotheses, with no awareness of scenario, metric name, host, or any other train-set artifact. The three new numeric constants are pure numerical-stability guards with values uncorrelated to baseline metrics. Tests use synthetic metric names t
hack_detector (reject): The change produces a NET NEGATIVE outcome (mean F1 Δ-0.0018, FPs Δ+2) and violates the proposer's own pre-declared success bar (F1 >= 0.140, no regression on casino_postgresql/059_fortnite — both regressed by -0.055 and -0.017 respectively). The single isolated win on ehr_pgbouncer cannot justify a generalized observation-model rewrite that ships net-negative on the headline metric while the auth
algorithm_expert (approve): Diff is a minimal, in-place coefficient change to the existing BOCPD predictive: it adds a scalar AR(1) lag term (ρ, prev_x) to the per-run-length Gaussian, with a one-time O(W) ρ estimate at warmup-end and a guarded clamp ±0.95. Interface, factory, catalog, file/header, state-key pattern, helper-reuse, and non-blocking contract are all preserved. Per-tick cost is bounded (~+3 FLOPs/hypothesis), n

Working tree reverted; no commit.

Budget: This iter: 4,911,793 in / 57,933 out (~~$44.64). Run total: 103,899,495 tokens (~~$805.90) (20.8% of 500,000,000 ceiling). Model mix: Opus 37%, Sonnet 63%.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T07:03:22}

ellataira · 2026-04-28T07:03:33Z

🏁 phase_exit [requires ack]

Phase 1 plateaued after 5 consecutive non-improving iterations. Best score so far: 0.2210. Pivot #4.

Banned (newly added): ['ar1-predictive-bocpd', 'dispersion-shift-conover', 'martingale-conformal-postfilter', 'multiscale-local-window', 'runlength-entropy-bocpd']
Banned (cumulative): ['anomaly-rank-postfilter', 'bocpd-nig-conjugate', 'hampel-robust-prefilter', 'page-hinkley-heteroscedastic', 'wasserstein-distance-changepoint', 'density-ratio-postfilter', 'hac-autocorrelation-correction', 'linear-detrend-postfilter', 'permutation-bootstrap-postfilter', 'spectral-residual-detector', 'cross-series-common-mode-rejection', 'evt-spot-self-calibrating-threshold', 'kernel-mmd-changepoint', 'matrix-profile-discord', 'seasonal-adaptive-hazard-bocpd', 'ar1-predictive-bocpd', 'dispersion-shift-conover', 'martingale-conformal-postfilter', 'multiscale-local-window', 'runlength-entropy-bocpd']

⚠️ max_pivots_before_halt=4 reached with zero ships across the run. The proposer has exhausted 4 structurally-different families and the gates have rejected all of them. This is a signal that either: (a) the baseline is genuinely hard to improve on the current scenario set, (b) the gates are too strict, or (c) the candidate directions need human-level redirection. Writing .coordinator/inbox.md with a specific steer will be used by the proposer on the next run.

_{— Claude (coordinator harness) · 72edc0d258 · 2026-04-28T07:03:32}

ellataira and others added 8 commits April 20, 2026 11:10

[observer] Add custom gensim directory (#49657)

22015b1

### What does this PR do? This adds a new lookahead directory for custom gensim scenarios owned by q branch like this [one](DataDog/gensim-episodes#93). ### Motivation ### Describe how you validated your changes ### Additional Notes

[q-branch] Add list episodes command (#49785)

bcb50f0

### What does this PR do? Small utility because I'm lost sometimes... ### Motivation ### Describe how you validated your changes ### Additional Notes

coord: run-log start (full, 20260427T1644)

64131ea

Merge remote-tracking branch 'origin/q-branch-observer' into claude/o…

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…bserver-full-20260427T1644

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