Auto Push logo

Auto Push

Community
luongnv89
auto-push

Generate a commit message, stage all changes, and push to remote after scanning for secrets, large files, and protected-branch risks. Skip for opening PRs, code review, or cutting releases/tags.

Overview

Publisherluongnv89
Repositoryskills
Skill nameauto-push
Stars
124
Forks
18
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by luongnv89 on GitHub. Read the source before you install it.

Installation

Install the Auto Push 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.
  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/luongnv89/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/auto-push .claude/skills/auto-push
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Auto Push 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 Auto Push 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 Auto Push 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.

Commit and Push Everything

CAUTION: Stage ALL changes, commit, and push to remote. Use only when confident all changes belong together.

When to Use

Trigger this skill when the user asks to "commit and push everything", "ship this", "auto-push", or otherwise wants a one-shot stage-commit-push for the current working tree. Skip when they want PRs, code review, releases, or tags.

Sync Repo Before Edits

Before creating/updating/deleting files in an existing repository, sync the current branch with remote:

bash
branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin
git pull --rebase origin "$branch"

If the working tree is not clean, stash first, sync, then restore:

bash
git stash push -u -m "pre-sync"
branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin && git pull --rebase origin "$branch"
git stash pop

If origin is missing, pull is unavailable, or rebase/stash conflicts occur, stop and ask the user before continuing.

Instructions

Step 1: Analyze Changes

Run in parallel:

  • git status - Show modified/added/deleted/untracked files
  • git diff --stat - Show change statistics
  • git log -1 --oneline - Show recent commit for message style

Step 2: Run Safety Checks

❌ STOP and WARN if detected:

  • Secrets: .env*, *.key, *.pem, credentials.json, secrets.yaml, id_rsa, *.p12, *.pfx, *.cer
  • API Keys: Any *_API_KEY, *_SECRET, *_TOKEN variables with real values (not placeholders like your-api-key, xxx, placeholder)
  • Large files: >10MB without Git LFS
  • Build artifacts: node_modules/, dist/, build/, __pycache__/, *.pyc, .venv/
  • Temp files: .DS_Store, thumbs.db, *.swp, *.tmp

API Key Validation: Check modified files for patterns like:

bash
OPENAI_API_KEY=sk-proj-xxxxx  # ❌ Real key detected!
AWS_SECRET_KEY=AKIA...         # ❌ Real key detected!
STRIPE_API_KEY=sk_live_...    # ❌ Real key detected!

# ✅ Acceptable placeholders:
API_KEY=your-api-key-here
SECRET_KEY=placeholder
TOKEN=xxx
API_KEY=<your-key>
SECRET=${YOUR_SECRET}

✅ Verify:

  • .gitignore properly configured
  • No merge conflicts
  • Correct branch (warn if main/master)
  • API keys are placeholders only

Step 3: Confirm and Execute

Present a short summary as a dry-run preview, then proceed directly when safety checks pass. If any safety check fails, STOP and ask for explicit user confirmation before continuing — never bypass a failed safety check without a confirmation prompt.

📊 Changes Summary:
- X files modified, Y added, Z deleted
- Total: +AAA insertions, -BBB deletions

🔒 Safety: ✅ No secrets | ✅ No large files | ⚠️ [warnings]
🌿 Branch: [name] → origin/[name]

Proceeding now: git add . → commit → push

When all safety checks pass, proceed directly without an additional yes/no confirmation prompt.

Step 4: Stage Files

Run sequentially:

bash
git add .
git status  # Verify staging

Step 5: Generate Commit Message

Analyze changes and create conventional commit:

Format:

[type]: Brief summary (max 72 characters)

- Key change 1
- Key change 2
- Key change 3

Types: feat, fix, docs, style, refactor, test, chore, perf, build, ci

Example:

docs: Update concept README files with comprehensive documentation

- Add architecture diagrams and tables
- Include practical examples
- Expand best practices sections

Step 6: Commit and Push

bash
git commit -m "$(cat <<'EOF'
[Generated commit message]
EOF
)"
git push  # If fails: git pull --rebase && git push
git log -1 --oneline --decorate  # Verify

Step 7: Report Success

✅ Successfully pushed to remote!

Commit: [hash] [message]
Branch: [branch] → origin/[branch]
Files changed: X (+insertions, -deletions)

Expected Output

On success, the skill outputs a confirmation block:

✅ Successfully pushed to remote!

Commit: abc1234 feat: add login page with OAuth support
Branch: feature/auth → origin/feature/auth
Files changed: 4 (+112, -8)

If safety checks block the push, the skill outputs:

❌ Push blocked — secrets detected

  .env: OPENAI_API_KEY=sk-proj-xxxxx (real key)

Action required: remove or rotate the key, then re-run /auto-push.

Acceptance Criteria

The skill run is successful when all of the following hold:

  • Working tree synced with origin (git fetch ran; rebase clean or stash/pop completed without conflicts)
  • Safety scan reported no secrets, no real API keys, and no large binaries — or the user explicitly confirmed each warning
  • Branch is correct (warned and confirmed if main/master)
  • Commit message follows the conventional format from Step 5
  • git push exited 0 and git log -1 shows the new commit on the remote-tracking ref
  • Final success report printed (commit hash, branch, file counts)

Handle Edge Cases and Errors

For the edge-case table, per-phase step-completion report format, error-handling guidance, and alternative workflows (selective staging, interactive git add -p, PR flow), see references/edge-cases-and-reports.md.

Remember: This skill already scans for secrets, large files, and branch risk in Step 2 and proceeds automatically once those checks pass — no extra manual review step is inserted. Use individual git commands instead if you want more control over what gets committed.

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 Auto Push AI skill do?

Generate a commit message, stage all changes, and push to remote after scanning for secrets, large files, and protected-branch risks. Skip for opening PRs, code review, or cutting releases/tags.

Why use Auto Push on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/luongnv89/skills/tree/main/skills/auto-push. 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 Auto Push?

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 Auto Push?

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

Is the Auto Push AI skill free?

Yes. It is published on GitHub by luongnv89 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.

View all

Set up your own AI workspace now

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