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Ccf Integrity Auditor

CommunityPopular
mikubaka88
ccf-integrity-auditor

Audit existing CCF claims, numbers, terminology, and citations against supplied or verified evidence. Use for 引用核验, claim审计, 数字一致性, and BibTeX/context checks. Full scientific review belongs to ccf-paper-reviewer; new literature discovery belongs to ccf-literature-searcher.

Overview

Publishermikubaka88
RepositoryCCFA-Skills
Skill nameccf-integrity-auditor
Stars
2.6K
Forks
116
Bundled files
1
LicenseMIT
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 mikubaka88 on GitHub. Read the source before you install it.

Installation

Install the Ccf Integrity 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.
  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/mikubaka88/CCFA-Skills.git /tmp/CCFA-Skills
mkdir -p .claude/skills
cp -r /tmp/CCFA-Skills/ccf-integrity-auditor .claude/skills/ccf-integrity-auditor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ccf Integrity 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 Ccf Integrity 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 Ccf Integrity 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.

CCF Integrity Auditor

Family File Contract

Before writing, resolve the canonical output and one stable working directory per task/artifact. Reuse explicit or established task paths; otherwise use project-root ccfa-workfiles/<purpose>/<artifact-id>/, with source/, assets/, cache/, and build/ only as needed. Update current files in place; do not scatter intermediates or create iteration copies. Preserve inputs and required evidence; clean only verified disposable files created by this task. Use UTF-8 text I/O and check Chinese text after saving or rendering. For file work, apply artifact-contracts.md and reuse the same paths across skill transitions.

Collaboration Contract

Before specialist execution, read and apply ccf-humanization first, then ccf-common. At every handoff, reuse their applicable active rules or refresh missing/changed ones. Both preflights are required even without prose; detailed editing, experiment, and maintenance modes run only when relevant.

Keep one integrating owner and actively use other skills to resolve missing prerequisites or check material findings. Reuse applicable evidence; do not skip necessary groundwork to save tokens. Before finalizing, integrate contributions and verify affected results. Follow the conditional cooperation routes; avoid unrelated stages and duplicate reports.

Core Rule

Trace each important claim to supplied evidence, each number to supplied results, and each citation to a real cited work and a supported citation context. Mark unsupported items instead of repairing them by invention.

Modes

  • claim-audit: claim-support and result-to-claim consistency.
  • numeric-audit: numbers, units, table/figure/text agreement, deltas, and metric direction.
  • citation-audit: already cited papers, BibTeX metadata, duplicate keys, DOI/arXiv/venue sanity, and citation-context support.
  • full: all integrity checks.

Workflow

  1. Identify supplied manuscript, figures/tables/results, bibliography, ccfa.yaml, and requested audit mode.
  2. Build a claim-evidence matrix and mark each claim as supported, partially supported, unsupported, overstated, or unclear.
  3. Cross-check the reported values within the requested scope across text, tables, figures, captions, abstracts, and conclusions. Use deterministic arithmetic for deltas, units, metric direction, and rounding. Distinguish not comparable from inconsistent.
  4. For citation audit, verify the identity and context support of existing citations through primary sources; metadata existence alone does not establish support. Batch independent identifiers when possible. Seek new literature only when requested; broad discovery belongs to ccf-literature-searcher.
  5. For any questionable citation, separate metadata problems from context-support problems.
  6. Hand off to ccf-paper-reviewer for full scientific judgment and to ccf-paper-writer for safe wording edits.
  7. If the numbers and claims are consistent but the figure/table layout, caption placement, palette, float order, or rendered readability is weak, hand off to ccf-visual-composer.

Output Contract

text
Mode:
Artifacts checked:
Claim-evidence matrix:
Numeric consistency findings:
Citation metadata findings:
Citation-context findings:
Severity:
Safe edit suggestions:
Next CCFA owner:
No-invention status:

Execution Boundaries

Follow ../ccf-common/references/handoff-modes.md, ../ccf-common/references/task-modes.md, and ../ccf-common/references/privacy-and-evidence.md. Finish the checkable portions when an attachment or source is missing. Report exact file/page/table locations, affected values or claims, evidence, and severity; mark unverified coverage separately from failures. An audit request does not authorize manuscript rewriting. Use existing authorization for explicitly requested fixes and preserve raw measurements.

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 Ccf Integrity Auditor AI skill do?

Audit existing CCF claims, numbers, terminology, and citations against supplied or verified evidence. Use for 引用核验, claim审计, 数字一致性, and BibTeX/context checks. Full scientific review belongs to ccf-paper-reviewer; new literature discovery belongs to ccf-literature-searcher.

Why use Ccf Integrity Auditor on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mikubaka88/CCFA-Skills/tree/main/ccf-integrity-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 Ccf Integrity 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 Ccf Integrity Auditor?

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

Is the Ccf Integrity Auditor AI skill free?

Yes. It is published on GitHub by mikubaka88 under the MIT 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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