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Evidence Auditor

Community
WILLOSCAR
evidence-auditor

Use when `paper-review` needs a claim-by-claim evidence gap report grounded in an extracted claim ledger.

Overview

PublisherWILLOSCAR
Repositoryresearch-units-pipeline-skills
Skill nameevidence-auditor
Stars
513
Forks
39
Bundled files
1
Links
  • 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 WILLOSCAR on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/evidence-auditor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/WILLOSCAR/research-units-pipeline-skills.git /tmp/research-units-pipeline-skills
mkdir -p .claude/skills
cp -r /tmp/research-units-pipeline-skills/.codex/skills/evidence-auditor .claude/skills/evidence-auditor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evidence Auditor 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 Evidence Auditor 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 Evidence Auditor 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.

Evidence Auditor

Triggers & routing

  • Trigger: evidence audit, missing evidence, unsupported claims, 审稿证据审计, 证据缺口.
  • Use when: paper-review 流程中,需要逐条检查 claim 的证据链、缺 baseline、评测薄弱点。
  • Skip if: 缺少 claims 输入(例如还没有 output/CLAIMS.md)。
  • Network: none.
  • Guardrail: 只写“缺口/风险/下一步验证”,不要替作者补写论述或引入新主张。

Transforms a claim ledger into a gap report for paper-review.

Input

  • output/CLAIMS.md

Output

  • output/MISSING_EVIDENCE.md
  • output/EVIDENCE_AUDIT.jsonl (review-evidence-gap.v1)

Contract

Each gap block should include:

  • claim reference
  • what evidence is already present
  • what is missing or weak
  • minimal fix
  • severity

Each JSONL record must retain claim_id and a stable gap_id so the final review can cite the exact failure rather than paraphrasing an unlocated concern.

Script boundary

scripts/run.py should:

  • iterate existing claims only
  • classify the likely evidence risk
  • write actionable, bounded gap items

It should not invent new claims or rewrite the manuscript.

Acceptance

  • every claim has a corresponding evidence note or gap item
  • minimal fixes are actionable and concrete
  • structured records join back to every claim_id

Non-goals

  • manuscript rewriting
  • novelty assessment
  • recommendation writing

Bundled files

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

Frequently asked questions

What does the Evidence Auditor AI skill do?

Use when `paper-review` needs a claim-by-claim evidence gap report grounded in an extracted claim ledger.

Why use Evidence Auditor on TypingMind?

Because you install it once and use it with any model. Evidence Auditor 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 Evidence Auditor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/evidence-auditor. 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 Evidence Auditor?

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 Evidence Auditor?

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

Is the Evidence Auditor AI skill free?

It is published on GitHub by WILLOSCAR. Check the repository for licensing terms. 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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