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feat(analyze): aggregate batch error-analysis tool (closes #159)#255

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feat(analyze): aggregate batch error-analysis tool (closes #159)#255
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feat/error-analysis

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Aggregate batch error-analysis tool (closes #159)

clawbench-analyze reads a directory of completed run outputs (<run>/data/interception.json, optional <run>/reward.json) and produces an aggregate error analysis, reusing the per-run classifier (classify_run):

  • Stage-1 (interception) + Stage-2 (judged) rates
  • Failure taxonomyresult_category counts (intercepted / infra_failure / zero-action / not-intercepted …)
  • Per-category Stage-1 breakdown (category from task metadata, else task-id segments)
  • Interceptor false-positive check — 0-action runs that were intercepted (should be 0) — a core validity signal that the benchmark isn't luck-passable
  • Self-report gap — runs where the agent claimed success but actually failed (justifies interception-based, not self-report, scoring)
clawbench-analyze --runs-dir <batch-output> [--out report.md] [--json]

Self-contained, unit-tested on fixtures (5 tests); ruff + pyright clean; full suite green. Complements clawbench-batch/clawbench-rescore.

clawbench-analyze reads a directory of completed run outputs and produces an
aggregate error analysis, reusing the per-run classifier (classify_run):
- Stage-1 (interception) and Stage-2 (judged) rates
- failure taxonomy (result_category counts: intercepted / infra_failure /
  zero-action / not-intercepted ...)
- per-category Stage-1 breakdown (category from task metadata or task-id segments)
- interceptor false-positive check (0-action runs that were intercepted -> should
  be 0), a core validity signal
- self-report gap (agent claimed success but the run actually failed)

Markdown or --json output. Self-contained + unit-tested on fixtures (5 tests);
ruff + pyright clean; suite green.
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feat(analysis): error analysis + per-task failure breakdown + agent-capability insights from results

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