[benchmark corpus] Resolve Python cross-function `batch` FN: relabel sibling helpers or accept as unrecoverable

[AndresL230]

Context

Follow-up to #117 (FN #1) and PR #132. #117 bundled two C1 false negatives; #132 recovered the unbatched_parallel FN but deferred the Python cross-function batch FN after attempting and reverting a fix.

The reverted attempt (a module-scope (provider, methodChain) batching pass in src/scanner/python-waste-detector.ts) proved this is not a detector gap — it's a corpus-labeling inconsistency. This issue tracks the corpus-side decision that #117's original "design sketch" did not anticipate.

⚠️ This issue belongs in recost-dev/extension-benchmark (where the fixtures live), filed here only because that repo is outside the current automation scope. Please move/mirror it there.

The problem

The corpus labels exactly one batch FN:

• flask-mixed-providers/src/providers/anthropic_helper.py:11 — two calls to _client.messages.create(...) across two module-level functions (summarize, summarize_with_style).

But sibling helpers in the same fixture — openai_helper.py, cohere_helper.py — have structurally identical two-calls-across-two-functions shapes and are not labeled as batch findings. Any cross-function pass precise enough to fire on the Anthropic helper also fires on the siblings → 6 FPs, batch precision drops to 14.3%. No AST signal distinguishes the labeled case from the unlabeled-but-identical ones (would require cross-file call-graph signal the scanner doesn't currently expose).

Decision needed — pick one

Option A — Relabel (recover the FN). Add batch-finding labels to the structurally-identical sibling helpers (openai_helper.py, cohere_helper.py, and any others) so the cross-function pass becomes precise. Then re-implement the reverted (provider, methodChain) module-scope pass in python-waste-detector.ts.

Option B — Accept (drop the FN from the recall target). Formally mark the anthropic_helper.py:11 batch case as unrecoverable without cross-file call-graph signal in the corpus, removing it from the batch recall denominator. python-waste-detector.ts stays byte-identical to main.

Acceptance criteria

• Decision recorded (A or B) with rationale, in extension-benchmark.
• If A: sibling helpers labeled consistently; the reverted module-scope pass re-implemented; npm run benchmark shows batch at TP 1+ / FP 0 / FN 0; no regression to the 7 existing C1 tests; per-type precision stays 100%.
• If B: corpus annotation marks the case unrecoverable; batch recall target adjusted; baseline.json regenerated so the row is no longer counted as an outstanding FN.

Do NOT

Re-add the (provider, methodChain) pass without first resolving the labeling — #132 already proved it regresses batch precision to 14.3% on the current corpus.

Links

• Parent: [Findings] Recover the two C1 false negatives — cross-function batch + inline-parallel unbatched #117
• Reverted attempt + analysis: feat(wave4): recover unbatched_parallel FN; defer Python batch FN (#117) #132

[AndresL230]

Moved to recost-dev/extension-benchmark#8, as this issue itself flagged (the corpus-labeling decision belongs where the fixtures live). The do-not-reintroduce note about the reverted python-waste-detector.ts pass is preserved there.