mcpbeat

Flashrag Evidence

foryourhealth111-pixel/flashrag-evidence

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

4k tokens
context cost
the whole folder, loaded on every use
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
2583
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/foryourhealth111-pixel/Vibe-Skills --skill flashrag-evidence

What comes with it

12 666 bytes besides the instruction
scripts/flashrag_evidence.py

The instruction itself

7 sections, as written by the author

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)

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

Workflow (Lite, no heavy deps)

  • Run the evidence retriever script:
  • Windows PowerShell:
  • python C:\Users\羽裳\.codex\skills\flashrag-evidence\scripts\flashrag_evidence.py --query "…" --topk 8
  • (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
  • 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)
  • 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).

How to use it

Copy the folder

Take foryourhealth111-pixel/flashrag-evidence from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.