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Scene/entity extraction, summarizer, AI providers, embeddings
AuthN/Z, roles, tenancy/org scoping, API keys, credentials
Plans, entitlements, AI spend accounting and caps
Incident correlation, linking, lifecycle, severity, corr_debug
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behavior-bug
Wrong product behavior; the instrument reads it correctly
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measurement-bug
Corrupts the recording/instrument (debug data, evals, health checks), not behavior
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Reference: logan/server-26#105
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Closes #80, closes #95.
intelligence.py writes only the primary scene's embedding and severity to calls/{id}. _build_context read them back off the call doc, so every non-primary scene of a multi-scene call was correlated against scene 1's semantic vector and severity rung — a scene about a different event scored on the embedding path against the wrong incident, and could inherit a minor/moderate/major severity it never had, clearing the creation gate on borrowed weight. Same defect and same fix as the #87 coords leak.
Changes
Testing: full c2-core suite green (295 passed) on a sandboxed Linux venv. drb-correlation-review verdict: ship after a pytest run (done).
Not closed here — tracked separately: #102 (llm_correlator._call_block still reads the whole-call transcript per scene — remaining leg), #103 (divergence veto on Nss stale severity). #5 prompt change isunmeasured — needs a scoped correlation-only window with Summaries/Vocab off.
intelligence.py writes only the primary scene's embedding and severity to calls/{id}. _build_context read them back off the call doc, so every non-primary scene of a multi-scene call was correlated against scene 1's semantic vector and severity rung: a scene about a different event scored on the embedding path against the wrong incident, and could inherit a minor/moderate/major severity it never had, clearing the creation gate on borrowed weight. Same defect and same fix as the #87 coords leak. - _build_context / preview_correlation / correlate_call: take embedding and severity as params; drop the call_doc.get() fallbacks. A scene that passes none has none, and is judged thin on its own signal. - upload.py: both scene loops pass scene["embedding"] / scene["severity"]; _correlate_with_consensus forwards them. The no-scene unclassified branch passes neither (correct: no scene, judged thin). - recorrelation_sweep: passes the call doc's stored values explicitly (whole-call re-link, link-only, so a borrowed severity cannot create). - intelligence.py: SCENE DETECTION prompt tightened toward one scene (server-26#5, partial) - MULTIPLE only for genuinely separate events, "when unsure, one scene", plus a not-a-new-scene list. - test_incident_identity.py: +2 regression tests mirroring the #87 test. Full c2-core suite green (295 passed). #5 prompt change is unmeasured - needs a scoped correlation-only window. Known remaining legs, tracked separately: llm_correlator._call_block still reads the whole-call transcript per scene; content-divergence veto skips on a None embedding. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>