Flashrag Evidence

CommunityPopular

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.

Overview

Publisher	foryourhealth111-pixel
Repository	`Vibe-Skills`
Skill name	`flashrag-evidence`
Stars	3.7K
Forks	326
Bundled files	1
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by foryourhealth111-pixel on GitHub. Read the source before you install it.

Installation

Install the Flashrag Evidence AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/flashrag-evidence
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

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

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills.git /tmp/Vibe-Skills
mkdir -p .claude/skills
cp -r /tmp/Vibe-Skills/bundled/skills/flashrag-evidence .claude/skills/flashrag-evidence

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flashrag Evidence in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Flashrag Evidence on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Flashrag Evidence is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/flashrag_evidence.py12 KB

Frequently asked questions

What does the Flashrag Evidence AI skill do?

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

Why use Flashrag Evidence on TypingMind?

Because you install it once and use it with any model. Flashrag Evidence is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Flashrag Evidence in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/flashrag-evidence. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Flashrag Evidence?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Flashrag Evidence?

As many as you like. As long as a model supports skills, you can use Flashrag Evidence with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Flashrag Evidence AI skill free?

Yes. It is published on GitHub by foryourhealth111-pixel under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

FlashRAG Evidence (VCO)

When to use

Inputs

Default corpus (evidence plane)

Workflow (Lite, no heavy deps)

Outputs

Notes (non-redundancy)

Bundled files

Frequently asked questions

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