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Docs Guard

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amElnagdy
docs-guard

Review generated or changed documentation before it ships — READMEs, API references, docstrings, PHPDoc/JSDoc, changelogs, tutorials, and doc sites. Best used reactively after an agent writes or edits docs, after code changes documented behavior, or before publishing docs. Use when the user says 'review the docs', 'is this documentation accurate', 'update the docs', 'write a README', 'document this API', 'add a docstring', or 'add a changelog entry'. Core job: verify every referenced function, flag, endpoint, config key, and code sample against the source; catch docs-vs-code drift; strip filler and unverifiable claims. DO NOT USE for production code review (use clean-code-guard), test review (use test-guard), marketing copy or blog posts, prose style editing of non-technical writing, or documentation site theming.

Overview

PublisheramElnagdy
Repositoryguard-skills
Skill namedocs-guard
Stars
1.2K
Forks
141
Bundled files
6
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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by amElnagdy on GitHub. Read the source before you install it.

Installation

Install the Docs Guard 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/amElnagdy/guard-skills.git /tmp/guard-skills
mkdir -p .claude/skills
cp -r /tmp/guard-skills/skills/docs-guard .claude/skills/docs-guard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docs Guard 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 Docs Guard 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 Docs Guard 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.

Docs Guard

You are reviewing generated or changed documentation before it ships. Apply the rules below as a guard pass after the first documentation pass. The core principle: documentation is a set of claims about a codebase, and every claim is checkable. Your job is to check them.

These rules exist because AI agents document from memory of how APIs usually look, not from the code in front of them. Published research: half of AI answers to programming questions contain incorrect information, and models produce valid invocations for infrequent APIs barely a third of the time — yet the prose sounds authoritative either way. Readers cannot tell verified docs from hallucinated docs. You can, because you have the source.

How to use this skill

Guard-pass mode (recommended): after documentation or docstrings have been generated or edited, verify every claim against the source and run the self-check before delivery.

Live mode (explicit): when the user invokes this skill before writing docs, verify before you write — read the actual implementation, then document what it does. Run the self-check before delivery.

Review mode (the user asks you to review, audit, or fact-check docs): walk references/review-checklist.md against the target docs and produce a findings report with file:line evidence. Do not rewrite in review mode unless asked.

Adapt to the project first

  1. Read the project's agent instructions (CLAUDE.md, AGENTS.md) and any docs style guide. Project conventions win on conflict.
  2. Identify the docs surfaces that must move together: README, reference docs, docstrings, changelog, examples, config samples. A change to one usually owes a change to others (Rule 6).
  3. Note the documented version policy: which versions does the project support, and where are features version-tagged?

The Rules

Accuracy — must fix

  1. Every referenced symbol must exist. Every function, method, class, hook, CLI command, flag, endpoint, config key, env var, and file path mentioned in the docs gets verified against the actual source, CLI help output, route table, or schema — by reading it, not recalling it. The verification procedure is in references/verification.md. An unverifiable reference does not ship.

  2. Every code sample must work. Imports resolve, APIs exist with the documented signatures (names, argument order, defaults, return shape), and the sample runs outside the author's machine — no hardcoded local paths, no real credentials, no implicit prior state. Sample rules: references/code-samples.md.

  3. Document the code's actual behavior, not its intended behavior. Read the implementation before describing it. Where code and comments/specs disagree, the code is the truth — and flag the disagreement to the user instead of silently picking a side.

  4. No unverifiable claims. Performance numbers, compatibility matrices, scale limits, and "production-ready" assertions require a source in the repository (benchmark script, CI matrix, changelog entry) or they come out. "Fast" is marketing; "O(n log n), benchmarked in bench/sort.md" is documentation.

Versioning and drift

  1. Versions are explicit. Features, flags, and behaviors state the version that introduced them when the project tracks versions. Prerequisites are pinned or ranged, never "latest". Deprecated items say so, with the replacement.

  2. A code change owes a docs change. When editing code whose behavior is documented — rename, signature change, new default, removed flag — update every doc surface that mentions it in the same change. Grep the docs for the old symbol before finishing.

Substance — should fix

  1. No filler, no slop. Delete: docstrings that paraphrase the signature ("Gets the user by ID" above get_user_by_id), sections that restate their heading, marketing adjectives in technical prose ("powerful", "seamless", "blazingly fast"), and intro padding ("In this section, we will explore…"). A docstring earns its place by adding contracts the signature cannot express: units, ranges, error conditions, side effects, threading/ordering guarantees.

  2. Don't paraphrase upstream docs. Link to external documentation instead of restating it — paraphrased upstream docs drift the moment upstream changes. Document only your project's relationship to the external thing (which subset you use, what you configure differently).

  3. Examples cover the failure path too. A tutorial that only shows the happy path documents half the API. Show what the error looks like and what the caller should do — using the error types the code actually raises (verify per Rule 1).

Structure — worth noting

  1. Navigation tells the truth. Headings describe their sections, the table of contents matches the actual headings, internal links and anchors resolve, and there are no TODO stubs or "coming soon" sections in published docs — unwritten sections are removed, not promised.

Self-check before delivery

  1. List every symbol, flag, endpoint, config key, and path your docs mention. Did you verify each one against the source in this session — not from memory?
  2. Would every code sample run on a clean machine? Did you check each import and signature?
  3. Any number, compatibility claim, or superlative without a repo-verifiable source?
  4. If this change touched code: did you grep all docs surfaces for the old names?
  5. Any docstring that just restates the signature? Any section that restates its heading?
  6. Do all internal links and anchors resolve?

If any answer is wrong, fix it before showing the user.

Reporting format (review mode)

**Rule N violation** in `docs/path.md:<line or section>`
- Claim: <what the docs say>
- Reality: <what the code/CLI/schema actually has, with file:line>
- Fix: <one sentence>

Lead with Rule 1–4 findings (false claims), then drift, then substance. If a doc is clean, say so in one line — accuracy deserves credit.

Severity guide

  • Must fix: Rules 1–4 — false documentation is worse than no documentation; readers act on it
  • Should fix: Rules 5–9 — drift debt and noise that buries the signal
  • Worth noting: Rule 10 — navigation and polish

References

What this skill does not do

  • Review the code itself — clean-code-guard's jurisdiction. This skill reviews what the docs claim about the code.
  • Generate documentation strategy or information architecture from scratch — it guards accuracy and substance, not scope decisions.
  • Enforce a prose style guide — tone belongs to the project; truth belongs to this skill.

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 Docs Guard AI skill do?

Review generated or changed documentation before it ships — READMEs, API references, docstrings, PHPDoc/JSDoc, changelogs, tutorials, and doc sites. Best used reactively after an agent writes or edits docs, after code changes documented behavior, or before publishing docs. Use when the user says 'review the docs', 'is this documentation accurate', 'update the docs', 'write a README', 'document this API', 'add a docstring', or 'add a changelog entry'. Core job: verify every referenced function, flag, endpoint, config key, and code sample against the source; catch docs-vs-code drift; strip fi...

Why use Docs Guard on TypingMind?

Because you install it once and use it with any model. Docs Guard 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 Docs Guard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/amElnagdy/guard-skills/tree/master/skills/docs-guard. 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 Docs Guard?

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 Docs Guard?

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

Is the Docs Guard AI skill free?

Yes. It is published on GitHub by amElnagdy 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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