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flashrag-evidence

Search local VCO/vibe documentation, configuration, and skill descriptions for evidence behind rules or recommendations. Retrieve ranked excerpts with file paths and line numbers so explanations can point directly to the supporting source passages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Local evidence retrieval (FlashRAG-style) for VCO/vibe: search protocols/config/skills docs and return citeable snippets with file+line anchors.

foryourhealth111-pixel/Vibe-Skills

실행 점수 미검증

설치 방법 보기

이럴 때 유용합니다

  • Finding the source of a VCO rule
  • Explaining why a skill pack was selected
  • Checking configuration thresholds and their meaning
  • Finding supporting passages in project-local documents

포함된 파일(2)

  • SKILL.md2.7 KB
  • scripts/flashrag_evidence.py12.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

FlashRAG Evidence (VCO)

When to use

Use this skill when you need grounded, citeable evidence from local documentation/configuration to support VCO decisions or recommendations, especially for:

  • VCO routing / pack selection rationale
  • Protocol compliance (think/do/review/team/retro)
  • Config semantics (thresholds, overlays, governance)
  • “Show me where this rule comes from” / “give me the exact snippet”

This skill is not a replacement for GitNexus (code dependency graph) or web search. It focuses on local docs and config.

Inputs

  • Query: what you’re trying to verify (short, concrete)
  • Optional: corpus root(s) to search (defaults below)

Default corpus (evidence plane)

  1. VCO core docs/config inside ~/.codex/skills/vibe/:
    • protocols/, config/, references/, scripts/router/
  2. Skills catalog (~/.codex/skills/**/SKILL.md) for tool capability evidence
  3. (Optional) Project-local VCO overlays under the current workspace, if present

Workflow (Lite, no heavy deps)

  1. Run the evidence retriever script:

    • Windows PowerShell:
      • python C:\Users\羽裳\.codex\skills\flashrag-evidence\scripts\flashrag_evidence.py --query "…" --topk 8

  2. (Optional) Enable a faster FlashRAG-style BM25 backend (bm25s)

    • Preflight (checks vendoring + env; does NOT read secrets):
      • pwsh C:\Users\羽裳\.codex\skills\vibe\scripts\ruc-nlpir\preflight.ps1
    • Manually create an isolated venv for the vendored runtime and install only the minimal packages you need. The old install-upstreams.ps1 auto-install path has been removed on purpose.
    • Use bm25s engine:
      • C:\Users\羽裳\.codex\_external\ruc-nlpir\.venv\Scripts\python.exe C:\Users\羽裳\.codex\skills\flashrag-evidence\scripts\flashrag_evidence.py --engine bm25s --query "…" --topk 8

  3. Use the returned snippets as P5 evidence:

    • [Command] the exact command you ran
    • [Output] the top snippets (path + line anchor)
    • [Claim] the conclusion you draw (only what the evidence supports)

  4. If coverage is low:

    • Expand --roots to include the project workspace
    • Increase --topk
    • Fallback: targeted rg -n on the most likely file(s)

Outputs

The script prints ranked evidence items:

  • path + line (1-based) for quick navigation
  • score for ranking
  • snippet (short, safe to quote)

Notes (non-redundancy)

  • If you need code call chains / blast radius, use GitNexus overlays (not this).
  • If you need latest web facts, use web search / deep research tools (not this).

리뷰

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