coord run-log (full) — 2026-05-01 14:03#50229
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iter 46 · Evaluating against detectors:
Budget: Run total: 505,854,501 tokens (~$7274.20) (101.2% of 500,000,000 ceiling). Model mix: Opus 92%, Sonnet 8%. — Claude (coordinator harness) · |
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Gitlab CI Configuration Changes
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Updated: .gitlab/distribution.yml
Changes Summary
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ℹ️ Diff available in the job log.
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Go Package Import DifferencesBaseline: e5b320d
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🚨 iter 46 · Gate failures: fp_egregious=98 > 93 (3× baseline 31) and absolute > 20 Top 5 |ΔF1| scenarios:
Observed mean F1 0.2230 vs baseline 0.3007 (Δ-0.0777). Total FPs 31 → 98 (Δ+67). Working tree reverted; no commit. Budget: This iter: 10,596,705 in / 41,747 out ( — Claude (coordinator harness) · |
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iter 47 · Evaluating against detectors:
Budget: Run total: 520,432,762 tokens (~$7494.79) (104.1% of 500,000,000 ceiling). Model mix: Opus 92%, Sonnet 8%. — Claude (coordinator harness) · |
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🔔 iter 47 · Reason: The candidate is miswired: the catalog registers a stub detector (NewAnomalyStrengthDedupDetector, kind=componentDetector, defaultEnabled=true) whose Detect returns an empty DetectionResult, while the actual implemented mechanism (StrengthDedupCorrelator in anomaly_correlator_strength_dedup.go) has NO catalog entry at all. The implementer's own DONE summary admits "stage1 stub registered". Running --only anomaly_strength_dedup will target the stub and produce no anomalies, so the scenario eval can produce no scored-output difference attributable to the proposed mechanism. This also contradicts plan step 9 (correlator entry between passthrough and closing bracket) and step 12 (MUST NOT be enabled by default — the registered stub has defaultEnabled: true). Checks:
Required before eval:
Working tree reverted; moving on. Budget: This iter: 4,570,153 in / 27,307 out ( — Claude (coordinator harness) · |
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iter 48 · Evaluating against detectors:
Budget: Run total: 525,030,222 tokens (~$7565.39) (105.0% of 500,000,000 ceiling). Model mix: Opus 92%, Sonnet 8%. — Claude (coordinator harness) · |
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Static quality checks❌ Please find below the results from static quality gates Error
Gate failure full details
Static quality gates prevent the PR to merge! Successful checksInfo
On-wire sizes (compressed)
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🔔 iter 48 · Reason: The catalog entry for "pelt" is registered with defaultEnabled: true (component_catalog.go:209), but the proposer plan was explicit and emphatic that this MUST be false, citing prior tsslope rejection (exp-0039) for that exact inverted-flag pattern. The rrcf catalog entry comment (lines 176-181) confirms the harness uses defaultEnabled to define the prod-realistic baseline; flipping pelt on adds it to the baseline alongside bocpd, contaminates the candidate-vs-baseline contrast, and reproduces a known waste pattern. Otherwise the implementation is coherent (full PELT DP, Welford pre-gate, MAD-gated deviation check, alert lifecycle modeled on BOCPD) and would be worth evaluating, so this is a one-line fix rather than a skip. Checks:
Required before eval:
Working tree reverted; moving on. Budget: This iter: 8,991,556 in / 111,077 out ( — Claude (coordinator harness) · |
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iter 49 · Evaluating against detectors:
Budget: Run total: 534,196,618 tokens (~$7708.79) (106.8% of 500,000,000 ceiling). Model mix: Opus 92%, Sonnet 8%. — Claude (coordinator harness) · |
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🔔 iter 49 · Reason: pre_eval_gate response did not include primary_reason Checks:
Required before eval:
Working tree reverted; moving on. Budget: This iter: 8,315,914 in / 66,862 out ( — Claude (coordinator harness) · |
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iter 50 · Evaluating against detectors:
Budget: Run total: 544,371,229 tokens (~$7866.60) (108.9% of 500,000,000 ceiling). Model mix: Opus 92%, Sonnet 8%. — Claude (coordinator harness) · |
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❌ iter 50 · Mean F1 0.3007 → 0.1160 (Δ-0.1846). Reviewer verdicts:
Working tree reverted; no commit. Budget: This iter: 13,594,096 in / 96,452 out ( — Claude (coordinator harness) · |
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🔔 Phase 1 plateaued after 5 consecutive non-improving iterations. Best score so far: 0.2897. Pivot #7. Banned (newly added): ['anomaly-strength-dedup-correlator', 'cramer-von-mises-twosample-detector', 'glr-likelihood-ratio-postfilter', 'pelt-multi-changepoint-detector', 'sample-entropy-complexity-detector'] Coordinator auto-pivoting: the proposer will generate new candidates with the banned families filtered out. (Write — Claude (coordinator harness) · |
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iter 51 · Evaluating against detectors:
Budget: Run total: 558,061,777 tokens (~$8077.74) (111.6% of 500,000,000 ceiling). Model mix: Opus 93%, Sonnet 7%. — Claude (coordinator harness) · |
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❌ iter 51 · Mean F1 0.3007 → 0.1060 (Δ-0.1946). Reviewer verdicts:
Working tree reverted; no commit. Budget: This iter: 13,580,609 in / 89,105 out ( — Claude (coordinator harness) · |
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iter 52 · Evaluating against detectors:
Budget: Run total: 571,731,491 tokens (~$8288.14) (114.3% of 500,000,000 ceiling). Model mix: Opus 93%, Sonnet 7%. — Claude (coordinator harness) · |
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❌ iter 52 · Mean F1 0.3007 → 0.2546 (Δ-0.0461). Reviewer verdicts:
Working tree reverted; no commit. Budget: This iter: 13,328,771 in / 72,811 out ( — Claude (coordinator harness) · |
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iter 53 · Evaluating against detectors:
Budget: Run total: 589,274,859 tokens (~$8557.18) (117.9% of 500,000,000 ceiling). Model mix: Opus 93%, Sonnet 7%. — Claude (coordinator harness) · |
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🔔 iter 53 · Reason: pre_eval_gate response did not include primary_reason Checks:
Required before eval:
Working tree reverted; moving on. Budget: This iter: 6,551,476 in / 29,987 out ( — Claude (coordinator harness) · |
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iter 54 · Evaluating against detectors:
Budget: Run total: 595,856,322 tokens (~$8657.70) (119.2% of 500,000,000 ceiling). Model mix: Opus 93%, Sonnet 7%. — Claude (coordinator harness) · |
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💥 iter 54 · Error: Captured CLI stderr (tail): Working tree reverted; moving on. Budget: This iter: 13,368,166 in / 75,502 out ( — Claude (coordinator harness) · |
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iter 55 · Evaluating against detectors:
Budget: Run total: 609,299,990 tokens (~$8863.89) (121.9% of 500,000,000 ceiling). Model mix: Opus 93%, Sonnet 7%. — Claude (coordinator harness) · |
## Summary Rewrites `comp/observer/impl/patterns/` (Tokenizer + TokenListSignature) in the style of the upstream `pkg/logs/internal/decoder/preprocessor` tokenizer, while preserving every public type, token shape, signature string, and merge decision. All existing patterns tests pass unmodified. ### What changed - **Regex elimination.** All 8 package-level regexes (ISO/CLF date, time, IPv4, URI scheme, email, hex dump) replaced with hand-coded byte scanners. The fixed-shape prefix matchers run without `regexp` execution overhead or per-call submatch slice allocations. - **`charClass` lookup table.** 256-byte table with bit flags backs `isDigit`/`isAlpha`/`isAlphaNum`/`isHexByte`/`isWordChar`. - **First-byte dispatch in `matchAt`.** Digit lines skip URI/email/path matchers; alpha lines skip date/IPv4/path matchers; whitespace lines skip everything but `tryWhitespace`. - **Tokenizer scratch buffer.** Internal `[]Token` scratch is reused across calls; the returned slice is still a fresh exact-sized copy so callers (cluster patterns) can keep retaining it. - **`TokenListSignature` single-pass.** No longer materializes a temporary `[]string` of per-token signatures. - **Maps → switches.** `parseMonthAbbr`, `httpMethods`, `severityKeywords`, `validHTTPStatusCodes`. - **Interning.** `SpecialCharToken` interns its single-byte string (256-element table); `WhitespaceToken` interns small space-runs. - **`*Raw` token constructors.** `URIToken`/`AuthorityToken`/`PathQueryFragmentToken`/`PathToken`/`EmailToken` got `*Raw` variants that take the already-matched substring — saves the redundant `strings.Builder`/concat the public constructors do (the tokenizer always had the slice at hand and used to overwrite `.Value` afterward). - **Direct date format building.** Skips the old `q()`/`cleanDateFormat` quote-and-strip dance — cleaned form is built directly. ### What didn't change - Drain-style merge in `PatternClusterer` (ratio threshold + cross-signature-group fallback). - The `Token` struct shape (`Type` + `Value` + `extra` pointer). - `MessageSignature`/`Parse` (test-only entry points). ### Benchmarks **Patterns-only microbenchmark (15-line mix, single Tokenizer):** | Bench | Baseline | Now | Speedup | |---|---|---|---| | `Tokenize` | 305,680 ns / 306 allocs | 9,878 ns / 33 allocs | **31×** time, **9×** allocs | | `MessageSignature` | 323,161 ns / 385 allocs | 18,552 ns / 69 allocs | **17×** time, **5.6×** allocs | | `PatternClustererProcess` | 340,689 ns / 443 allocs | 18,432 ns / 108 allocs | **18×** time, **4.1×** allocs | **End-to-end (`BenchmarkLogExtraction_DiversePatterns`, full observer engine):** | series | Baseline ns/op | Now ns/op | Speedup | Allocs reduction | |---|---|---|---|---| | 50 | 1.63 ms | 0.46 ms | **3.5×** | −26% | | 200 | 6.04 ms | 1.89 ms | **3.2×** | −22% | | 500 | 15.49 ms | 4.71 ms | **3.3×** | −21% | | 2000 | 61.03 ms | 18.11 ms | **3.4×** | −21% | A new `tokenizer_bench_test.go` is included in the patterns package so future regressions are easy to spot. ## Test plan - [x] `go test ./comp/observer/impl/patterns/` passes - [x] `go test ./comp/observer/impl/...` passes - [x] `go vet ./comp/observer/...` clean - [x] Patterns and end-to-end benchmarks captured before/after
seriesKey is on the hot path for log ingestion (engine.IngestLog), detector loops (seriesDetectorAdapter.Detect, BOCPD/RRCF/Scan*), extractor metric emission (log_metrics_extractor, log_pattern_extractor), and contextRef bookkeeping. Profiling on quality_gate_container_logs (50 containers, ~10k logs/sec) showed seriesKey accounting for 33% of inuse heap. The previous form used four chained `+` concatenations plus a strings.Join inside joinTags, producing multiple intermediate strings per call. Replacing with a single strings.Builder pre-grown to the exact final length removes the intermediates and shrinks allocations on the hottest microbench (BenchmarkLogExtraction_DiversePatterns series=200) from 21048 to 20365 allocs/op.
… by SeriesRef seriesDetectorAdapter.Detect runs once per advance per wrapped SeriesDetector (BOCPD, RRCF, ScanMW, ScanWelch when wrapped). Two problems on the container-logs workload: 1. It called storage.ListSeries(...) on every Detect with no caching, while the SeriesDetectors themselves use the storage.SeriesGeneration() pattern (storage.go:684) to amortise that cost. The adapter now adopts the same cache-by-gen pattern. 2. It built a fresh seriesKey(meta.Namespace, meta.Name, meta.Tags) string per series per Detect just to use as a map key into lastVisibleCount. With container-bearing tag sets this is a real-world ~200 byte string allocated thousands of times per advance (visible in the heap profile under metricContextKey/ seriesKey). Switched the map to key by observer.SeriesRef, which storage hands out as compact, append-only ints (storage.go:217). Verified: tests in comp/observer/impl pass; BenchmarkReplayStoredData_* unchanged (the synthetic bench uses nil tags so the per-meta seriesKey allocation is small). Win materialises on the real container-logs path where tags-per-series are large and seriesGen churn from log_pattern_extractor was repeatedly invalidating the existing SeriesDetector caches anyway.
Trivial change: the upper bound is known under the lock, so a single preallocation removes the growslice cascade that ListSeries hits on large series counts. Pairs with the seriesDetectorAdapter cache (previous commit) to keep the worst-case ListSeries cost flat when seriesGen does churn.
…ise sourceTag
Two allocations per ingested log per emitted metric on the
engine.IngestLog hot path:
1. `tags := copyTags(m.Tags)` always copied even when sourceTag was
already in the slice. The copy is only needed to avoid mutating the
extractor's slice when we append. Reorder: check membership first,
copy-then-append only if needed. storage.Add canonicalises with its
own copy on first-write of a series, and seriesKey sorts an internal
copy when needed, so neither path mutates the input.
2. `sourceTag := "observer_source:" + source` allocated a fresh
string on every IngestLog call. Sources are a small bounded set
("logs", "profiles", ...) so memoise via an atomic.Pointer to a
copy-on-write map. Lock-free reads on the hot path; writes happen
the first time each source is seen.
Cumulative effect with the previous three commits on
BenchmarkLogExtraction_DiversePatterns series=200:
21048 -> 19804 allocs/op (-5.9%)
1775 -> 1745 KB/op (-1.7%)
10824 -> 10571 µs/op (-2.3%)
The SMP container-logs workload should see a larger win because real
tag sets are much fatter than the bench's single-tag synthetic data,
and the seriesDetectorAdapter cache change in the previous commit
amortises over per-advance ListSeries that the microbench doesn't
exercise.
Reproduces the always-on Observer's container-log overhead in CI: 50 busybox containers each emit apache-common-style log lines on stdout (~200/sec/container, ~10k logs/sec total). Logs management is OFF in datadog.yaml; only the comparison image's Observer ingests, isolating observer-on-logs overhead. Bounds: - memory_usage <= 370 MiB (220 MiB baseline + 150 MiB observer budget) - cpu_usage <= 500 mc (50% headroom over baseline observer budget) - intake_connections.current <= 6 Observer flags live in experiment.yaml.environment, not datadog.yaml, so the baseline agent (which doesn't recognise them) doesn't crash. Specifically: DD_OBSERVER_ANALYSIS_ENABLED=true # comparison runs the AD DD_OBSERVER_INGEST_METRICS_ENABLED=false # measure log path only Originally landed in smp-playground (PR #416) for fast iteration on experiment shape; ported in-tree so the SMP child pipeline picks it up automatically (--target-config-dir test/regression/) and grades the optimisations in this branch end-to-end on every CI run.
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💥 iter 654 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 9,235,503 in / 38,659 out ( — Claude (coordinator harness) · |
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iter 655 · Evaluating against detectors:
Budget: Run total: 7,026,710,689 tokens (~$105269.39) (1405.3% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 655 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 6,643,127 in / 41,007 out ( — Claude (coordinator harness) · |
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iter 656 · Evaluating against detectors:
Budget: Run total: 7,033,394,823 tokens (~$105372.11) (1406.7% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 656 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 11,534,320 in / 79,493 out ( — Claude (coordinator harness) · |
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iter 657 · Evaluating against detectors:
Budget: Run total: 7,045,008,636 tokens (~$105551.09) (1409.0% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 657 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 13,474,931 in / 65,341 out ( — Claude (coordinator harness) · |
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iter 658 · Evaluating against detectors:
Budget: Run total: 7,060,222,167 tokens (~$105784.96) (1412.0% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 658 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 13,802,092 in / 63,855 out ( — Claude (coordinator harness) · |
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iter 659 · Evaluating against detectors:
Budget: Run total: 7,074,088,114 tokens (~$105996.78) (1414.8% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 659 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 10,816,330 in / 56,284 out ( — Claude (coordinator harness) · |
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iter 660 · Evaluating against detectors:
Budget: Run total: 7,084,960,728 tokens (~$106163.25) (1417.0% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 660 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 10,882,546 in / 46,428 out ( — Claude (coordinator harness) · |
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iter 661 · Evaluating against detectors:
Budget: Run total: 7,097,562,612 tokens (~$106356.06) (1419.5% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 661 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 14,857,964 in / 101,717 out ( — Claude (coordinator harness) · |
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iter 662 · Evaluating against detectors:
Budget: Run total: 7,112,522,293 tokens (~$106586.56) (1422.5% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 662 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 16,377,152 in / 84,558 out ( — Claude (coordinator harness) · |
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iter 663 · Evaluating against detectors:
Budget: Run total: 7,128,984,003 tokens (~$106838.56) (1425.8% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 663 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 16,567,578 in / 110,048 out ( — Claude (coordinator harness) · |
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iter 664 · Evaluating against detectors:
Budget: Run total: 7,147,869,099 tokens (~$107129.78) (1429.6% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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🔔 iter 664 · Reason: pre_eval_gate response did not include primary_reason Checks:
Required before eval:
Working tree reverted; moving on. Budget: This iter: 8,784,582 in / 39,334 out ( — Claude (coordinator harness) · |
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iter 665 · Evaluating against detectors:
Budget: Run total: 7,156,693,015 tokens (~$107264.50) (1431.3% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 665 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 9,980,893 in / 68,347 out ( — Claude (coordinator harness) · |
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iter 666 · Evaluating against detectors:
Budget: Run total: 7,166,742,255 tokens (~$107419.34) (1433.3% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 666 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 12,696,394 in / 58,913 out ( — Claude (coordinator harness) · |
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iter 667 · Evaluating against detectors:
Budget: Run total: 7,181,900,211 tokens (~$107652.21) (1436.4% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 667 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 8,671,081 in / 37,097 out ( — Claude (coordinator harness) · |
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iter 668 · Evaluating against detectors:
Budget: Run total: 7,190,608,389 tokens (~$107785.06) (1438.1% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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💥 iter 668 · Stderr tail: Working tree reverted; moving on. Budget: This iter: 11,980,220 in / 49,186 out ( — Claude (coordinator harness) · |
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iter 669 · Evaluating against detectors:
Budget: Run total: 7,202,637,795 tokens (~$107968.45) (1440.5% of 500,000,000 ceiling). Model mix: Opus 97%, Sonnet 3%. — Claude (coordinator harness) · |
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Coordinator harness run-log.
fullclaude/observer-full-20260501T1403ella/claude-coordinator-harness(harness + observer; PR diff = ships only)q-branch-observerThis 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.