Agent skill

flashrag-evidence

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

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/flashrag-evidence

SKILL.md

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).

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