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Deliver bounded feature knowledge to reviews and update init workflow - #288
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Score prose terms before discarding description candidates
When a PR changes a new or otherwise unmapped path and its title/body describes the behavior using terms from the page prose rather than the exact feature ID or full title, this continue drops the page before the prose-overlap score on lines 212–213 is computed. Consequently, description-based retrieval returns no_match even for clearly relevant explanatory content, so the newly advertised related_knowledge context is absent unless path metadata or an exact title/feature token already matched; compute a bounded prose score before deciding that the candidate has no signal.
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Direct plans previously returned owner rule maps while feature-depth prose remained behind manual search/read. This change returns the most relevant explanatory knowledge automatically in Direct MCP, SDK and Agent review, using one repository-scoped reader with a two-document/6,000-character limit. Results expose source pins, missing depth facets and bounded followup reads; SDK references retain the plan snapshot and agent injection respects briefing ablation.
Initialization now writes reviewed feature/entry-point/glob hints without changing accepted prose or checkpoint proofs. Existing JiuwenSwarm feature pages receive the same hints, and init/review skills, Cursor instructions, playbook and specs include offline retrieval acceptance. Knowledge bodies and hard-rule routes are unchanged. The workflow checker also recognizes the heading-form rule IDs used by the owner rules.
Measured against merged baseline 2b66967: description+path probes deliver 79/79 feature explanations and 77/77 existing depth pages; paths-only probes deliver 77/79 features (ttse/worktree remain ambiguous). All 79 rule routes stay identical. Maximum background is 5,571 characters; local median retrieval overhead is about 1.9 seconds. These are catalog delivery measurements, not real PR recall or RQS gains. Breadth remains 2,043/2,199 files and checked depth 173/553 facets.
Validation: full offline
python -m pytest -q; post-review proof/depth/SDK/Agent regressions; CI knowledge-checker tests; both KB validators; doc links/citations and strict SPEC freshness; independent pinned-source audit; 158 actual Direct acceptance probes. Independent complete-diff review and--require-cleanpassed after fixing malformed proof digest/path acceptance. Final whole-tree validation also runs in PR CI.The 156 generated metadata-only page edits preserve original bodies. Generated audit JSON is intentionally included for reproducibility and is exempt from the production code-size budget; runtime source adds 256 lines, plus two checker lines and the offline audit tool. No new model provider, retrieval model call, extraction stage or persistent index is introduced.
Chinese report and reproducible evidence:
eval/knowledge-depth/jiuwenswarm-retrieval-improvement-cn.md,jiuwenswarm-retrieval-acceptance-20261002.json,jiuwenswarm-retrieval-baseline-20261002.json,jiuwenswarm-retrieval-depth-audit-20261002.json, andretrieval-independent-review-20261002.md.