Github Repo

Community

jdevalk

github-repo

Audits and improves GitHub repository quality — README structure, community health files, .github directory setup, issue/PR templates, metadata, releases, and branch hygiene. Use this skill whenever the user asks to improve, audit, review, or set up a GitHub repository, or when they mention things like "make my repo look professional", "add contributing guidelines", "set up issue templates", "improve my README", "clean up my repo", "prepare my repo for open source", or "make my GitHub project look good". Also trigger when working inside a git repository and the user asks about best practices for documentation, community files, or repository structure. If the user is in a repo directory and mentions README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT, LICENSE, .github, templates, or release tags, use this skill.

Overview

Publisher	jdevalk
Repository	`skills`
Skill name	`github-repo`
Stars	109
Forks	10
Bundled files	2
License	MIT
Links	Skill source Repository

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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by jdevalk on GitHub. Read the source before you install it.

Installation

Install the Github Repo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jdevalk/skills/tree/main/github-repo
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.

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/jdevalk/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/github-repo .claude/skills/github-repo

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github Repo 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 Github Repo 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 Github Repo 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.

GitHub Repository Optimizer

This skill audits a GitHub repository against best practices and generates or improves the files that make a repo look professional, welcoming, and well-maintained. It works with live repos (via gh CLI), local git directories, or files the user provides.

Implementation recipes live in AGENTS.md — read it when you need to generate or improve specific files. This file has the workflow and audit checklist.

Workflow

Gather repo context — Determine what we're working with and collect information
Run the audit — Score every aspect of the repo's public-facing quality
Generate or improve files — Produce the files that are missing or need work. Recipes are in AGENTS.md.
Metadata and readability pass — invoke metadata-check on the repo description and README blurb; readability-check on prose-heavy files.
Verify — Confirm the outputs are correct and complete

Phase 0: Gather Context

Key information to collect: repo name, description, language/framework, README existence and quality, which community health files exist, issue/PR template status, CI/CD status, release history, branch count. Use gh CLI if authenticated, otherwise read local files.

Phase 1: Audit

Score each category out of 10. For each, give 2–4 specific findings that quote the actual state.

README Quality (x/10)

Does the README exist? Is it well-structured with: project name and clear one-liner, badge row (build/license/version), description explaining what/why/who, quick start (install + first use in 3 steps or fewer), code examples, screenshots/demos if visual, configuration docs, contributing link, license mention? Is it under 500 lines with <details> for optional content?

Repository Metadata (x/10)

Description set and useful (not blank or "My awesome project")?
Topics/tags relevant and complete?
Website URL set if applicable?
Social preview image uploaded?
"Packages", "Environments", "Deployments" sections hidden if unused?

Community Health Files (x/10)

CONTRIBUTING.md — exists? Covers dev setup, code style, testing, PR process?
SECURITY.md — exists? Directs to private reporting channel, states response time?
CODE_OF_CONDUCT.md — exists? Contributor Covenant 2.1 is the standard.
LICENSE — exists in root? Appropriate for project type?
SUPPORT.md — exists? Separates bugs from support questions?
CHANGELOG.md — follows Keep a Changelog format?

For organizations: check for a .github repository with org-wide default health files.

Issue & PR Templates (x/10)

YAML-based issue forms (.github/ISSUE_TEMPLATE/*.yml) with at least bug report and feature request? Numbered filenames for ordering?
config.yml disabling blank issues and linking external support?
PR template with description, related issues (Closes #XXX), type-of-change checkboxes, testing checklist?
CODEOWNERS file defining reviewers per directory?

CI/CD & Automation (x/10)

GitHub Actions workflows for testing, linting, building? Passing status badges in README?
Dependabot or Renovate configured?
Code quality (CodeQL, linting actions)?
Stale issue management?

Releases & Branch Hygiene (x/10)

Tagged releases with changelogs? Semantic versioning?
Stale branches cleaned up?
.gitattributes with export-ignore?
Auto-release (semantic-release or release-please)?

Phase 2: Generate or Improve Files

Based on the audit, generate the files that are missing or need improvement. Always ask before overwriting. Read AGENTS.md for detailed recipes.

File generation order by impact: README.md, LICENSE, CONTRIBUTING.md, SECURITY.md, CODE_OF_CONDUCT.md, issue templates, PR template, CHANGELOG.md, SUPPORT.md, config files (dependabot.yml, CODEOWNERS, FUNDING.yml).

AGENTS.md sections: README generation, Community health files (CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), Issue templates, Organization-level setup (.github repo, org profile, private member profile, domain verification, rulesets).

Phase 2.5: Metadata and readability pass

Metadata pass — metadata-check skill. Run on the repo description (first ~100 chars show in search and profile cards) and the README's opening blurb.
Prose pass — readability-check skill. Run on every prose-heavy file — at minimum the README, plus CONTRIBUTING.md and SECURITY.md if you produced them.

Apply fixes directly. Skip for code-heavy files (issue templates, workflow YAML).

Phase 3: Verify

Verify files are in the correct locations.
Check that all internal links in the README work.
Confirm badge URLs are correctly formatted.
If gh is available, remind the user to update the repo's About section (description, topics, website URL, social preview) — these can't be set via files alone.
Summarize what was created/changed and what the user should do next.

Output format

Score table (6 categories, x/60), grouped findings quoting actual state, list of files generated/changed, and next steps for the user.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

AGENTS.md5 KB
evals/evals.json2 KB

Frequently asked questions

What does the Github Repo AI skill do?

Why use Github Repo on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jdevalk/skills/tree/main/github-repo. 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 Github Repo?

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 Github Repo?

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

Is the Github Repo AI skill free?

Yes. It is published on GitHub by jdevalk 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

GitHub Repository Optimizer

Workflow

Phase 0: Gather Context

Phase 1: Audit

README Quality (x/10)

Repository Metadata (x/10)

Community Health Files (x/10)

Issue & PR Templates (x/10)

CI/CD & Automation (x/10)

Releases & Branch Hygiene (x/10)

Phase 2: Generate or Improve Files

Phase 2.5: Metadata and readability pass

Phase 3: Verify

Output format

Bundled files

Frequently asked questions

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