7dddc1d706
- fetch_span: panic-fix on line_start > total / empty doc (return empty text + effective_end = line_start - 1 instead of out-of-bounds slice) - truncated: reserved for budget-driven truncation only; line range clamp signaled via effective_end < line_end - spec / SKILL.md / README: align rejection wording to "PDF / audio" (matches code; Image OCR allowed for span) - store: warning comment on list_chunk_ids_for_doc — chunk_id hash sort does NOT preserve document position; real fix is a chunks.ordinal column, tracked as follow-up - surrounding_chunks: saturating_add to defend against u32::MAX context arg on 32-bit targets - tests: line_start > total returns empty + chunk context at doc boundary clamps lower bound Deferred nits (follow-up): table-separator strict CommonMark form; MCP per-mode strict validation; CLI chunk_id truncation in plain output. None block correctness. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
47 lines
2.0 KiB
Markdown
47 lines
2.0 KiB
Markdown
---
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phase: P9
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component: kebab-cli + kebab-app + wire-schema
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task_id: p9-fb-35
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title: "Verbatim fetch (`kebab fetch <chunk_id|doc_id>`) — citation deep-link"
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status: completed
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target_version: 0.5.0
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depends_on: []
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unblocks: []
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contract_source: ../../docs/superpowers/specs/2026-04-27-kebab-final-form-design.md
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contract_sections: [§4 search, §5 storage, §10 UX]
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source_feedback: 사용자 도그푸딩 2026-05-06 — agent 가 search hit / citation 보고 더 깊이 파볼 때 raw chunk text + 주변 context 필요.
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---
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# p9-fb-35 — Verbatim fetch
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> ✅ **구현 완료.** 본 spec 은 구현 시점의 frozen 상태. post-merge deviation 은 [HOTFIXES.md](../HOTFIXES.md) 참조.
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상세 설계: `docs/superpowers/specs/2026-05-09-p9-fb-35-verbatim-fetch-design.md`.
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구현 계획: `docs/superpowers/plans/2026-05-09-p9-fb-35-verbatim-fetch.md`.
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## 증상 / 동기
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- search 결과의 snippet 은 highlight 중심 — agent 가 "이 chunk 의 전체 raw text" 또는 "이 chunk 앞뒤 context" 원함.
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- 현재 inspect 는 TUI 전용 — CLI / `--json` 으로 chunk 가져오는 명시 surface 없음.
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- citation 의 doc_id 만 받고 doc 전체 다시 ingest / read 하는 비효율.
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## Goal (skeleton)
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- `kebab fetch chunk <chunk_id> [--context N]` — chunk verbatim + 앞뒤 N 개 chunk.
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- `kebab fetch doc <doc_id>` — doc 전체 raw text.
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- `kebab fetch span <doc_id> <line_start> <line_end>` — 특정 라인 범위.
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- response wire schema `fetch_result.v1` 추가.
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## 후속 작업 — brainstorm 필요 항목
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- chunk_id / doc_id 노출 — 현재 search_hit.v1 에 있는지 확인 + 안정성.
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- context window — N 개 chunk vs N tokens.
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- doc 전체 fetch 의 size 제한 (fb-34 budget 과 통합).
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- pdf / audio 의 fetch — 텍스트 추출본 vs 원본 path. (image OCR 는 markdown line 으로 떨어져 span 허용.)
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## Risks / notes
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- wire schema 신규 — `fetch_result.v1` JSON Schema 추가.
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- 큰 doc fetch 시 budget control 필수 — fb-34 와 통합.
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- chunk_id 안정성 — re-ingest 후 chunk_id 변경되면 agent 의 citation stale.
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