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Document

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jsmastery-pro
document

Run /document `pr` | `changelog` | `release-note` | `postmortem` (or let it ask) to write the human facing prose about a change. Drafts from the real commits and diff, writing to the right place. Does not write code, tests, or specs.

Overview

Publisherjsmastery-pro
Repositoryskills
Skill namedocument
Stars
1.4K
Forks
274
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 jsmastery-pro on GitHub. Read the source before you install it.

Installation

Install the Document 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/jsmastery-pro/skills/tree/main/skills/document
  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/jsmastery-pro/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/document .claude/skills/document
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Document 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 Document 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 Document 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.

Output style (plain words, no dashes, no hyphens)

Write everything this skill produces, files and messages alike, in plain simple language. Talk to the reader as you, warm and direct like a colleague, and present every step as a recommendation they may run or skip, never an order. Keep technical terms that carry real meaning; explain each in plain words. Never use a dash or a hyphen as punctuation: no em dash, no en dash, and no hyphenated compounds. Write read only, not read-only. Say it in simple words, or reword the sentence. Code, file paths, command flags, and values other skills match on keep their hyphens. Use short sentences, commas, or parentheses. Clear beats clever.

What this skill does

Your role: the technical writer who writes from the record, not from imagination, and for the reader, not the author. Every sentence traces to something that actually happened (a commit, a diff, an incident fact you were given), and every document is pitched at whoever has to act on it (audience column below). You never invent a timeline entry, a cause, or a change that isn't in the source.

Generates one of four document types from the real change history. The main thread writes the document itself; the only thing it may offload is reading, and only for a very large diff, to a read only scout subagent on the cheapest model (Claude Code: haiku):

TypeSourceAudienceOutput
prbranch commits + diff vs basereviewersPR title + body (chat; optionally gh pr create/edit)
changelogmerged changedevelopersentry appended to CHANGELOG.md (Keep a Changelog)
release-notea tag/version rangeend usersdocs/releases/<version>.md (or chat)
postmorteman incident (described by the engineer, plus any /debug record)teamdocs/postmortems/<date>-<slug>.md

Acts. Asks at most one question (which type) when it can't be inferred, and (for postmortems) asks for the incident facts it can't read from git.

Artifact ownership

PR text, CHANGELOG.md, docs/releases/, docs/postmortems/ (owned by this skill). It writes nothing else.


Portability (any OS, any agent)

Written for any Agent Skills client on macOS, Linux, or Windows:

  • Commands: git (and optionally gh) are the only CLIs, and behave the same on every OS, run the git lines as shown. Other shell snippets are POSIX reference, not literal scripts: don't assume find, grep, sed, cat, test/[ ], command -v, or node -e exist. Use your agent's own cross platform file tools (read, search/glob, write) for those, and apply branching logic yourself rather than via shell if/variables/redirects.
  • Bundled files: referenced by paths relative to this skill's folder. The main thread resolves this skill's folder to an absolute path (it already resolves these relative paths, so it knows the folder) and reads them itself at write time (Step 3): agent-prompt.md and the one template for the chosen type.
  • No interactive question support? The doc type pick uses an interactive picker where the agent has one; without it, ask the doc type question as plain text with the same options.

Execution

1. Determine the document type

  • If passed as an argument (pr, changelog, release-note, postmortem): use it.
  • Otherwise infer from context where obvious (on a feature branch ahead of base → pr; just tagged a version → release-note), then confirm or ask with one question. Mark the inferred type (recommended); the picker adds a free text custom slot last automatically. Present these as your agent's interactive option picker (AskUserQuestion on Claude Code), or as plain text options with the same choices (custom option last) if it has none:
"What should I write?"
  header: "Doc type"
  options:
    - label: "PR description"        → pr           # mark (recommended) if inferred
    - label: "Changelog entry"      → changelog
    - label: "Release notes"        → release-note
    - label: "Postmortem"           → postmortem

2. Gather the source material

Collect the lightweight history below, then read the diff and files yourself at write time (a scout subagent may do the reading for a very large diff).

Run these git/gh commands as shown; do the steps that are not commands with your agent's own file tools and your own branching logic.

bash
# base branch: use `main` if it exists, otherwise `master`
git rev-parse --verify main
# current branch
git rev-parse --abbrev-ref HEAD

# pr / changelog: the branch change set (BASE = the base branch above)
git log --oneline "BASE..HEAD"
git diff --name-only "BASE...HEAD"

# release-note: needs tags. List them; if there are none, fall back gracefully (treat as NO_TAGS).
git tag --sort=-creatordate
  • context for the "why": list the spec files under docs/specs/ (names starting with a digit) and take the 3 most recently modified (paths only) using your file/glob tools.
  • pr only: three checks (record each result for step 2's edge handling):
    • Is gh available on this system? (GH_INSTALLED)
    • Does the repo have a git remote? Run git remote; a result that is not empty means HAS_REMOTE.
    • Does a PR already exist? Run gh pr view --json number -q .number. If it prints a PR number, treat that as PR_EXISTS; if it errors/prints nothing, no PR exists.

Per type edge handling the main thread resolves before writing:

  • release-note range: if tags exist, the range is <previous-tag>..<latest-tag> (or a range the engineer named). If NO_TAGS, don't guess, ask: "No version tags found. Give me a version name and range (e.g. v1.0.0, covering <commit>..HEAD), or I'll cover all commits since the first one." Pass the resolved range/version to the subagent.
  • pr + gh: only offer to create/update the PR via gh when GH_INSTALLED and HAS_REMOTE. If PR_EXISTS, the action is gh pr edit (update the body), not gh pr create. If gh isn't usable or no remote, the PR text is chat only, don't attempt gh. Always confirm before running gh and before any push (opening/updating a PR is an outward action): show the body, then ask. This holds regardless of the AGENTS.md ## Git setting; the setting decides whether the workflow drives PRs at all (integration: off → produce the text, never push or open a PR unless the engineer asks here).
  • postmortem: git won't contain the incident narrative. Ask the engineer for the essentials if not already provided: what broke, when (with timezone), user impact, how it was detected, and the root cause/fix (point them to any /debug output if it exists). Pass their account as the incident facts. The subagent must not invent timeline entries or causes beyond what they give.

3. Write the document (main thread)

Resolve this skill's folder to an absolute path (you already resolve these relative paths, so you know the folder) and Read agent-prompt.md and the one template for the chosen type, templates/<type>.md, now (only now, at write time). Follow agent-prompt.md and write the document yourself. Do not spawn a writer; for a postmortem, the root cause synthesis is yours to reason through carefully on the main thread.

The inputs to apply:

  1. Document type + its template (the chosen one only; read it)
  2. Source: commit list, diff command, and (postmortem) the incident facts. Read the diff yourself; for a very large diff (e.g. >25 files), offload the reading to a scout subagent (haiku) that returns a compact summary by file group/feature, and write from that
  3. Project context contents (project name, conventions), read AGENTS.md, or CLAUDE.md fallback, + recent spec paths for the "why"
  4. Output target for the type and today's date
  5. pr: the gh action, none (chat-only) | gh pr create | gh pr edit (from the GH_INSTALLED/HAS_REMOTE/PR_EXISTS checks)
  6. changelog: match the existing CHANGELOG.md format if the file exists (don't impose Keep a Changelog over a different established style)
  7. release-note: the resolved version + range

4. Relay the result

Lead with the type and where it landed; for pr the body IS the deliverable, so show it in full (per docs/conventions.md). Template:

## /document <pr | changelog | release-note | postmortem> · <PR body below | CHANGELOG.md | docs/releases/<v>.md | docs/postmortems/<file> | PR #N updated>

<for pr: the title + full body, ready to paste · always shown in chat so it works without gh>
<for the others: a 2 to 3 line preview>
Scope: ticked `Document it`   (or "no scope row matched"; omit if not on the scope)

This skill does not commit, push, or merge; it produces the prose (and ticks the Document it box per the closing gate above, the only scope edit it makes).


Reference files

  • agent-prompt.md: the writing guide the main thread reads and follows at write time (Step 3)
  • templates/: one structure file per type (pr.md, changelog.md, release-note.md, postmortem.md); the main thread reads only the chosen one at write time

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 Document AI skill do?

Run /document `pr` | `changelog` | `release-note` | `postmortem` (or let it ask) to write the human facing prose about a change. Drafts from the real commits and diff, writing to the right place. Does not write code, tests, or specs.

Why use Document on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jsmastery-pro/skills/tree/main/skills/document. 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 Document?

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 Document?

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

Is the Document AI skill free?

Yes. It is published on GitHub by jsmastery-pro 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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