P8: Quality — 100% coverage, error handling, graceful degradation
Fill remaining coverage gaps, comprehensive error messages, service health checks, idempotent everything, data versioning.
Closeout
All 5 issues closed. Test coverage pushed to 100% across src/ modules with the AST-based coverage oracle (test_ast_coverage.py) tracking every function, narwhalify decorator, and Expr call site. Service health checks added with graceful degradation (DuckDB, bib, API endpoints). Data versioning and snapshot support wired into the pipeline runner. Woodpecker CI pipeline gates on lint, test, and coverage thresholds. Error handling audit completed across all modules — consistent error types, actionable messages, no bare exceptions.
Issues resolved
- #31 — 100% test coverage across all src/ modules
- #32 — Service health checks with graceful degradation
- #33 — Data versioning and snapshot support
- #34 — Woodpecker CI pipeline for lint, test, coverage gate
- #35 — Comprehensive error handling audit
Residual
None. Coverage methodology further evolved in P26 (Pipeline Telemetry) and the new sem module (semantic coverage orchestration).
