Project Docs logo

Project Docs

Organization
vstorm-co
project-docs

Write or fix the documentation site — add a page, update one after a behaviour change, fix a dead link or a failing docs build, add a diagram or an icon, or wire a new page into the nav. Use whenever docs/ or mkdocs.yml is touched, and whenever a code change alters behaviour a page describes. make docs-build runs --strict, so a dead link fails CI.

Overview

Publishervstorm-co
Repositoryagenticos
Skill nameproject-docs
Stars
137
Forks
27
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vstorm-co on GitHub. Read the source before you install it.

Installation

Install the Project Docs 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/vstorm-co/agenticos/tree/main/.claude/skills/project-docs
  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/vstorm-co/agenticos.git /tmp/agenticos
mkdir -p .claude/skills
cp -r /tmp/agenticos/.claude/skills/project-docs .claude/skills/project-docs
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Docs 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 Project Docs 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 Project Docs 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.

The docs site

bash
make docs                       # serve on :8001 (DOCS_PORT=8002 if it is taken)
make docs-build                 # --strict; CI runs this, a dead link fails the build

docs/ is both the published site and the repository's own engineering notes — one copy, on purpose. A second copy of "how a capability works" written for outsiders is a copy that disagrees with the one contributors read. So: do not write a page that restates another page. mkdocs.yml's nav decides what an outside reader meets first; nothing is duplicated for them.

The same principle governs these skills. A skill routes to the doc and adds the operational layer; it does not paraphrase the doc.

Where to write when behaviour changes

The table in AGENTS.md under ## Documentation maps topic → page. Keep it current when you add a page.

Three things that silently render wrong

These have all shipped broken. Check the rendered page, not the Markdown.

Mermaid needs the custom fence. Without custom_fences on pymdownx.superfences, a ```mermaid block goes to the syntax highlighter and the reader gets the graph's source in a code box. Configured now — do not remove it.

Verifying is harder than it looks: Material renders into a closed shadow root, so the div.mermaid in the DOM is empty and querySelector('.mermaid svg') finds nothing. That is indistinguishable from a broken render. A screenshot is the only honest check. Mermaid itself loads from unpkg.com at page-view time, so diagrams do not render offline or behind a strict CSP.

Icons need pymdownx.emoji. Without the twemoji index, :material-download:{ .lg .middle } reaches the page as that literal string — the home page's grid cards rendered their own source for a while.

--strict does not validate anchors. A #fragment that matches no heading passes the build. Check fragments by hand, or with a script over the headings.

Search and link previews

scripts/mkdocs_hooks.py writes what a search result or a shared link reads from a page's head; Material writes only the title, description, canonical and hreflang.

  • seo_title in front matter replaces the <title> - at most 60 characters, starting with the page's own name. title stays short because the nav uses it.
  • description is the meta description and the card text - at most 160 characters. A page without one falls back to site_description.
  • Every page gets Open Graph and Twitter tags, with docs/assets/social-preview.png as the image from the site root in every locale.
  • A ## Frequently asked questions section becomes FAQPage structured data: each ### inside it is a question, the text up to the next one its answer. A translation must pin { #frequently-asked-questions }, which is how the hook finds the section in every language. Answers are published as plain text, so keep each one self-contained. backend/tests/test_mkdocs_seo.py covers the extraction.

Translate seo_title and description with the page; they are read by people searching in that language.

mkdocstrings

The API reference is generated from docstrings rather than written twice — this codebase puts its reasoning in docstrings, so a hand-written reference would be a worse copy of something already there.

The collector is static, and app/services/, app/api/ and app/worker/ have no __init__.py, so it cannot traverse into them: ::: app.services.foo fails the build. Reference those from prose with a source link until those packages are made explicit.

Because the reference is generated: when behaviour changes, fix the docstring. A prose page that repeats it will drift.

The seven tabs

AgenticOS · Features · Learn · Reference · Resources · About · Release Notes — FastAPI's arrangement, organised by what the reader is doing rather than by what a page is.

Learn is a sequence, not a bag: Get started → Build the agent → Put it in front of people → Keep it under control → the recipes. A page added there belongs at a position.

Files stay flat in docs/. The nav does the grouping. Those paths are named in AGENTS.md, in these skills, in scripts/docs_drift.py and in backend docstrings, so moving a file to get a prettier URL invalidates all of them.

release-notes.md is CHANGELOG.md, substituted at build time by scripts/mkdocs_hooks.py. That is a hook rather than a snippets include because snippets expand after every hook, so nothing could reach the included text to rewrite its docs/-prefixed links — and --strict fails on the docs/docs/… they resolve to.

Two pages are in the repository and not on the site

docs/ROADMAP.md and docs/about/design.md sit in exclude_docs beside design/, plans/ and audits/. Delivery state written in board shorthand and the six decisions a contributor needs before their first change are read by somebody who has already chosen to work on this; published, they put an internal status report in a tab a prospective user meets first.

A published page that links to either one fails --strict, because an excluded file is not built and the link resolves to nothing. Link them by GitHub blob URL instead - docs/about/index.md and docs/reference/capabilities.md are the two that do.

Adding a page

  1. Write it in docs/ (or docs/howto/, docs/reference/).
  2. Add it to nav in mkdocs.yml, at the position it belongs at — a page outside the nav is a build warning under --strict.
  3. Cross-link it from the pages a reader arrives from, and from AGENTS.md's table.
  4. make docs-build and check the anchors.

Voice

Use second person and present tense for user instructions. Explain behaviour and relevant reasons; distinguish verified facts from uncertainty. Choose prose, lists or tables according to what helps the reader.

  • Use sentence case headings, preserving product names and acronyms.
  • Keep paragraphs within the limit enforced by scripts/check_docs_paragraphs.py. Split by idea; use an admonition when a reader needs a warning before acting.
  • Add a recap only when it helps a reader retain the decisions from a long page. Do not repeat short pages or force a fixed number of bullets.

Icons

app/core/catalog/icons/<name>.svg is served by GET /catalog/icons and drawn for a catalog entry or provider whose id matches and which no compiled-in icon set carries. The file's own colours are ignored — it renders as a currentColor silhouette, unlike the compiled-in marks, which carry their brand's colour where it reads on both themes. See icons/README.md.

Frequently asked questions

What does the Project Docs AI skill do?

Write or fix the documentation site — add a page, update one after a behaviour change, fix a dead link or a failing docs build, add a diagram or an icon, or wire a new page into the nav. Use whenever docs/ or mkdocs.yml is touched, and whenever a code change alters behaviour a page describes. make docs-build runs --strict, so a dead link fails CI.

Why use Project Docs on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vstorm-co/agenticos/tree/main/.claude/skills/project-docs. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Project Docs?

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 Project Docs?

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

Is the Project Docs AI skill free?

Yes. It is published on GitHub by vstorm-co 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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