Update Readme logo

Update Readme

Community
gupsammy
update-readme

This skill should be used when the user asks to "update my README", "refresh the README", "README is outdated", "sync README with the codebase", "improve my README", "keep README up to date", "fix the README", "my README is stale", "update the readme file", "README needs updating", "update readme from git history", or "readme is out of date".

Overview

Publishergupsammy
RepositoryClaudest
Skill nameupdate-readme
Stars
275
Forks
16
Bundled files
Instructions only
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 gupsammy on GitHub. Read the source before you install it.

Installation

Install the Update Readme 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/gupsammy/Claudest/tree/main/plugins/claude-coding/skills/update-readme
  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/gupsammy/Claudest.git /tmp/Claudest
mkdir -p .claude/skills
cp -r /tmp/Claudest/plugins/claude-coding/skills/update-readme .claude/skills/update-readme
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Update Readme 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 Update Readme 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 Update Readme 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.

Update README

Refresh an existing README.md using current codebase state, git history, and changelog intelligence. Always updates CHANGELOG.md first so changelog content is available when revising README sections.

Step 1 — Check README Existence

Glob for README.md, readme.md, and Readme.md in the working directory.

If not found, or if the file has fewer than 5 lines of real content:

  • Inform the user no substantial README was found
  • Invoke Skill: claude-coding:make-readme
  • Stop — make-readme handles creation from scratch

If a substantial README exists: continue.

Step 2 — Update Changelog

Invoke Skill: claude-coding:make-changelog.

make-changelog detects fill mode automatically — it adds only versions missing since the last documented entry. If the repo has no git history, make-changelog will report an error; note it and continue without changelog context.

Step 3 — Parallel Research

Record the current README line count before edits.

Launch the three agents below in a single message (all in parallel):

Agent A — README Audit (subagent_type: Explore)

Prompt:

Read README.md. For each section (every H1/H2/H3 heading), record:
- Section name and approximate line count
- Stale content: version numbers, paths, commands, or features that look incorrect
- Placeholder text never replaced (e.g. "YOUR_USERNAME", "TODO", angle-bracket values)
- Thin sections with fewer than 3 lines of real content

Also identify which standard sections are MISSING:
installation, usage, configuration, API reference, contributing, license.

Return structured notes:
- existing_sections: list of heading names
- stale_items: list of {location, description} objects
- missing_sections: list
- thin_sections: list

Agent B — Codebase Scan (subagent_type: Explore)

Prompt:

Scan the working directory to extract:
- Project name and current version from the first found manifest:
  package.json, pyproject.toml, Cargo.toml, go.mod, .claude-plugin/plugin.json
- Primary language and framework (file extensions, config files)
- Top-level directory structure, max 2 levels deep
- Key public-facing files: entry points, config templates, example files, CLI scripts
- Documentation files beyond README: CONTRIBUTING.md, docs/, ARCHITECTURE.md, etc.

Return: project_name, version, language, framework, structure_summary,
key_files (paths), extra_docs (paths).

Agent C — Git History Since Last README Touch (subagent_type: Explore)

Prompt:

Run: git log --follow -1 --format="%ai" -- README.md
This gives the date README.md was last committed.
If README.md has no git history, use the initial commit date:
  git log --reverse --format="%ai" | head -1

Then run: git log --since="[date from above]" --format="%s" --no-merges

Categorize each commit subject into:
- new_features: new capabilities users can invoke
- breaking_changes: removed or incompatible changes
- deprecations: features flagged for future removal
- significant_fixes: user-visible bug fixes
- other: everything else

Skip: merge commits, CI/CD changes, formatting/whitespace, version-bump commits.

Return: readme_last_updated (ISO date), changes_since (object with 5 category lists).

Wait for all three agents to complete before Step 4.

Step 4 — Read Updated Changelog

Read CHANGELOG.md and extract the most recent version section (the first ## [x.y.z] block). This provides structured change context for README sections like Features.

Step 5 — Synthesize and Update

Apply targeted updates to README.md. Preserve existing style, header format, badge patterns, and overall structure — do not restructure unless clearly broken.

Apply in this priority order — highest-confidence fixes first, judgment-heavy additions last, because objective errors (wrong version, broken path) have deterministic answers while structural additions require codebase context to get right:

  1. Version/badge updates — update all version numbers and shields.io badge URLs to the version from Agent B
  2. Stale content — correct outdated paths, commands, flags, or removed features flagged by Agent A
  3. Placeholder cleanup — replace any unfilled placeholders with real values from Agent B
  4. New features — add or expand the Features section using Agent C's new_features list and the latest CHANGELOG section
  5. Missing sections — add any standard sections identified by Agent A as absent, with minimal viable content drawn from Agent B's codebase scan
  6. Thin sections — expand underdeveloped sections using Agent B context

If no updates are needed after applying all criteria, skip edits and proceed to Step 6.

For each change, make the smallest edit that achieves accuracy. Use Edit for targeted section updates — it preserves git blame and is safer for incremental changes. Use Write only if more than 60% of the file changes, because at that point the document is being regenerated, not updated.

Step 6 — Report

Output a diff summary after writing:

  • Line count: N → M lines
  • Sections updated: list with one-line description of each change
  • Sections added: list
  • Sections removed: list with reason (if any)
  • Version bumped: old → new (if applicable)
  • Changelog: versions added by make-changelog

Frequently asked questions

What does the Update Readme AI skill do?

This skill should be used when the user asks to "update my README", "refresh the README", "README is outdated", "sync README with the codebase", "improve my README", "keep README up to date", "fix the README", "my README is stale", "update the readme file", "README needs updating", "update readme from git history", or "readme is out of date".

Why use Update Readme on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gupsammy/Claudest/tree/main/plugins/claude-coding/skills/update-readme. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Update Readme?

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 Update Readme?

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

Is the Update Readme AI skill free?

It is published on GitHub by gupsammy. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇