FlashRAG Evidence (VCO)

SkillSearch

Lets your agent search local docs and return citeable snippets with file and line anchors.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the FlashRAG Evidence (VCO) skill

About this capability

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

What this skill tells your AI

The instructions your AI receives, as published by foryourhealth111-pixel/vibe-skills in bundled/skills/flashrag-evidence/SKILL.md and read by ahel’s review.

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).

Signals

GitHub stars
3k
Forks
277
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
flashrag-evidence
Source
github.com/foryourhealth111-pixel/vibe-skills