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Keeping Git Repos Clean

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wdm0006
keeping-git-repos-clean

Prevents, detects, and remediates files that should never be committed — secrets (.env, API tokens, hardcoded credentials) and dev artifacts (build output, scratch databases, editor/OS files). Covers .gitignore (and why it does not untrack), git rm --cached, auditing tracked files, history scrubbing, and credential rotation. Use when a repo has committed secrets or junk, when setting up a new repo's ignore rules, or when reviewing what a repo actually tracks.

Overview

Publisherwdm0006
Repositorypython-skills
Skill namekeeping-git-repos-clean
Stars
111
Forks
17
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by wdm0006 on GitHub. Read the source before you install it.

Installation

Install the Keeping Git Repos Clean 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/wdm0006/python-skills/tree/main/skills/common/git-hygiene
  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/wdm0006/python-skills.git /tmp/python-skills
mkdir -p .claude/skills
cp -r /tmp/python-skills/skills/common/git-hygiene .claude/skills/keeping-git-repos-clean
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Keeping Git Repos Clean 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 Keeping Git Repos Clean 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 Keeping Git Repos Clean 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.

Keeping Git Repos Clean

Two classes of files keep ending up in repos: secrets and dev artifacts. Both are cheap to prevent and expensive to clean up after the fact, because git history is forever and public repos publish everything.

The one rule everyone forgets

.gitignore does NOT untrack files that are already committed. Adding a path to .gitignore only prevents future untracked files from being staged. A file git is already tracking keeps getting committed regardless. This bites repeatedly: a .env is listed in .gitignore but was committed before the rule existed, so it keeps shipping.

To actually stop tracking a file while keeping your local copy:

bash
git rm --cached path/to/file        # untrack, leave working-tree copy in place
git rm -r --cached some/dir/        # for a directory
echo "path/to/file" >> .gitignore   # then ignore it so it doesn't come back
git commit -m "Stop tracking <file>; add to .gitignore"

--cached is the important flag — plain git rm deletes the working copy too.

Audit what a repo actually tracks

Don't trust .gitignore to tell you what's clean — read the index directly:

bash
git ls-files | grep -iE '\.(env|pem|key|p12|profraw|log|bak|db|sqlite3?)$'
git ls-files | grep -iE '(^|/)(\.DS_Store|~\$|todo\.db|node_modules/|__pycache__/)'
git ls-files '*.db' '*.sqlite*'                 # scratch databases
git ls-files | xargs -I{} du -h {} | sort -rh | head   # surprisingly large tracked files

Usual suspects seen across real repos:

  • Secrets: .env with a live token, hardcoded AWS_*/DB creds in a settings module, SECRET_KEY = "CHANGEME"/"foobar" placeholders shipped to prod.
  • Build artifacts: LaTeX .aux/.toc/.log/.synctex.gz/.pdf, LLVM *.profraw, compiled binaries, htmlcov/, dist/, *.egg-info/.
  • Scratch / personal artifacts: todo.db and other tool-local SQLite scratch DBs, editor backups (*.backup, *.bak, ~$*.docx Word lock files), stray *.log.
  • OS noise: .DS_Store, Thumbs.db.

Secrets need more than git rm

Removing a secret from HEAD does not remove it from history — git log -p and the commit that introduced it still expose it. Three things must happen, in order, and the first is the only one that actually protects you:

  1. Rotate the credential. Treat any secret that ever touched a remote as compromised. Issue a new token/key/password and revoke the old one. Do this first — the leaked value is public the moment it was pushed.
  2. Untrack going forward (git rm --cached + .gitignore + .env.example documenting which vars are needed, with placeholder values only).
  3. Scrub history if required (git filter-repo --invert-paths --path .env, or BFG) and force-push. This rewrites SHAs and disrupts collaborators, so it's usually a deliberate maintainer step done after rotation — not an automated PR.

A PR that does (2) and (3) but skips (1) gives false comfort: the value is still valid and still in history clones/forks. Always call out rotation as the required human follow-up.

"Committed" means "published"

For public repos — and especially static sites deployed with path: '.' (GitHub Pages uploads the entire repo) — every tracked file is fetchable at a public URL. A scratch todo.db at the repo root of a brochure site is served at /todo.db. Before committing to any public repo, assume anyone can download it.

Prevent it: global ignore + a secret scanner

Per-developer noise (editor files, OS files, tool scratch DBs like todo.db) should be ignored globally, not in every project's .gitignore — that way it never lands anywhere:

bash
git config --global core.excludesFile ~/.gitignore_global
printf '%s\n' '.DS_Store' '*.swp' 'todo.db' '*.profraw' >> ~/.gitignore_global

Block secrets at commit time with a pre-commit hook so they never reach history:

yaml
# .pre-commit-config.yaml
repos:
  - repo: https://github.com/gitleaks/gitleaks
    rev: v8.18.0
    hooks: [{id: gitleaks}]
  - repo: https://github.com/Yelp/detect-secrets
    rev: v1.5.0
    hooks: [{id: detect-secrets, args: ["--baseline", ".secrets.baseline"]}]

A starter project .gitignore (commit this):

gitignore
# Secrets / local config
.env
.env.*
!.env.example
*.pem
*.key

# Python build/test artifacts
__pycache__/
*.py[cod]
build/
dist/
*.egg-info/
.coverage
htmlcov/
.pytest_cache/

# Scratch / OS / editor
*.db
*.sqlite
*.sqlite3
*.profraw
*.log
*.bak
*.backup
.DS_Store
~$*

Verification can dirty the tree

Compilers, test runners, and asset pipelines often write into the checkout even when the command is only meant to verify a change. They may create unignored cache files or regenerate a tracked distributable such as a PDF or compiled CSS. A green command does not mean the working tree still contains only your change.

Bracket verification with status checks and stage only reviewed paths:

bash
git status --short
make test                         # or the project's real build command
git status --short
git diff -- path/you/changed
git add path/you/changed          # never sweep in generated files with git add -A
git diff --cached --check
git diff --cached --stat

If a tool necessarily produces noisy output, run it in a disposable copy of the checkout. This preserves a real build while keeping generated files away from the patch:

bash
scratch_dir=$(mktemp -d)
rsync -a --exclude .git ./ "$scratch_dir/"
(cd "$scratch_dir" && make build)

When verification modifies a tracked generated output that is intentionally out of scope, restore that exact path only after reviewing its diff:

bash
git diff -- docs/manual.pdf
git restore -- docs/manual.pdf

Do not use a broad restore/reset to clean up: the checkout may already contain someone else's work. Also do not rely on git stash as cleanup for untracked artifacts; ordinary stashes omit them, and even --include-untracked can collide with files regenerated before stash pop. Prevent or remove known generated paths explicitly instead.

Checklist

Audit:
- [ ] `git ls-files` reviewed for secrets, build output, scratch DBs, OS files
- [ ] No live credentials in tracked source or .env
- [ ] No surprisingly large/binary tracked files

Remediate (if dirty):
- [ ] Secret rotated/revoked FIRST (history is public the moment it was pushed)
- [ ] `git rm --cached` + .gitignore entry for each offending file
- [ ] .env.example documents required vars with placeholder values only
- [ ] History scrub flagged as a maintainer follow-up if the secret is in history

Prevent:
- [ ] Project .gitignore covers secrets, build artifacts, OS/editor noise
- [ ] Global core.excludesFile catches per-developer scratch files
- [ ] gitleaks / detect-secrets pre-commit hook installed
- [ ] Verification bracketed by `git status --short`; only reviewed paths staged

For scanning source code for vulnerabilities and hardcoded-secret patterns, see the auditing-python-security skill — this skill is about what git tracks.

Frequently asked questions

What does the Keeping Git Repos Clean AI skill do?

Prevents, detects, and remediates files that should never be committed — secrets (.env, API tokens, hardcoded credentials) and dev artifacts (build output, scratch databases, editor/OS files). Covers .gitignore (and why it does not untrack), git rm --cached, auditing tracked files, history scrubbing, and credential rotation. Use when a repo has committed secrets or junk, when setting up a new repo's ignore rules, or when reviewing what a repo actually tracks.

Why use Keeping Git Repos Clean on TypingMind?

Because you install it once and use it with any model. Keeping Git Repos Clean 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 Keeping Git Repos Clean in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wdm0006/python-skills/tree/main/skills/common/git-hygiene. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Keeping Git Repos Clean?

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 Keeping Git Repos Clean?

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

Is the Keeping Git Repos Clean AI skill free?

Yes. It is published on GitHub by wdm0006 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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