Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
日本語の概要は準備中です。原文の説明を表示しています。
Use on every code change — commit structure, branching, history hygiene, and versioning. Apply when committing work, opening or splitting a branch, writing commit messages, cutting a release, or recovering from a bad history state.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Attribution: Sourced from addyosmani/agent-skills by Addy Osmani, licensed MIT. Modified for this collection.
Git is your safety net. Treat commits as save points, branches as sandboxes, and history as documentation. With AI agents generating code at high speed, disciplined version control is the mechanism that keeps changes manageable, reviewable, and reversible.
Always. Every code change flows through git.
Keep main always deployable. Work in short-lived feature branches that merge back within 1-3 days. Long-lived development branches are hidden costs — they diverge, create merge conflicts, and delay integration. DORA research consistently shows trunk-based development correlates with high-performing engineering teams.
main ──●──●──●──●──●──●──●──●──●── (always deployable)
╲ ╱ ╲ ╱
●──●─╱ ●──╱ ← short-lived feature branches (1-3 days)
This is the recommended default. Teams using gitflow or long-lived branches can adapt the principles (atomic commits, small changes, descriptive messages) to their branching model — the commit discipline matters more than the specific branching strategy.
Each successful increment gets its own commit. Don't accumulate large uncommitted changes.
Work pattern:
Implement slice → Test → Verify → Commit → Next slice
Not this:
Implement everything → Hope it works → Giant commit
Commits are save points. If the next change breaks something, you can revert to the last known-good state instantly.
Each commit does one logical thing:
# Good: Each commit is self-contained
git log --oneline
a1b2c3d Add task creation endpoint with validation
d4e5f6g Add task creation form component
h7i8j9k Connect form to API and add loading state
m1n2o3p Add task creation tests (unit + integration)
# Bad: Everything mixed together
git log --oneline
x1y2z3a Add task feature, fix sidebar, update deps, refactor utils
Commit messages explain the why, not just the what:
# Good: Explains intent
feat: add email validation to registration endpoint
Prevents invalid email formats from reaching the database.
Uses Zod schema validation at the route handler level,
consistent with existing validation patterns in auth.ts.
# Bad: Describes what's obvious from the diff
update auth.ts
Format:
<type>: <short description>
<optional body explaining why, not what>
Types:
feat — New featurefix — Bug fixrefactor — Code change that neither fixes a bug nor adds a featuretest — Adding or updating testsdocs — Documentation onlychore — Tooling, dependencies, configDon't combine formatting changes with behavior changes. Don't combine refactors with features. Each type of change should be a separate commit — and ideally a separate PR:
# Good: Separate concerns
git commit -m "refactor: extract validation logic to shared utility"
git commit -m "feat: add phone number validation to registration"
# Bad: Mixed concerns
git commit -m "refactor validation and add phone number field"
Separate refactoring from feature work. A refactoring change and a feature change are two different changes — submit them separately. This makes each change easier to review, revert, and understand in history. Small cleanups (renaming a variable) can be included in a feature commit at reviewer discretion.
Target ~100 lines per commit/PR. Changes over ~1000 lines should be split. See the splitting strategies in code-review-and-quality for how to break down large changes.
~100 lines → Easy to review, easy to revert
~300 lines → Acceptable for a single logical change
~1000 lines → Split into smaller changes
main (always deployable)
│
├── feature/task-creation ← One feature per branch
├── feature/user-settings ← Parallel work
└── fix/duplicate-tasks ← Bug fixes
main (or the team's default branch)feature/<short-description> → feature/task-creation
fix/<short-description> → fix/duplicate-tasks
chore/<short-description> → chore/update-deps
refactor/<short-description> → refactor/auth-module
For parallel AI agent work, use git worktrees to run multiple branches simultaneously:
# Create a worktree for a feature branch
git worktree add ../project-feature-a feature/task-creation
git worktree add ../project-feature-b feature/user-settings
# Each worktree is a separate directory with its own branch
# Agents can work in parallel without interfering
ls ../
project/ ← main branch
project-feature-a/ ← task-creation branch
project-feature-b/ ← user-settings branch
# When done, merge and clean up
git worktree remove ../project-feature-a
Benefits:
Agent starts work
│
├── Makes a change
│ ├── Test passes? → Commit → Continue
│ └── Test fails? → Revert to last commit → Investigate
│
├── Makes another change
│ ├── Test passes? → Commit → Continue
│ └── Test fails? → Revert to last commit → Investigate
│
└── Feature complete → All commits form a clean history
This pattern means you never lose more than one increment of work. If an agent goes off the rails, git reset --hard HEAD takes you back to the last successful state.
After any modification, provide a structured summary. This makes review easier, documents scope discipline, and surfaces unintended changes:
CHANGES MADE:
- src/routes/tasks.ts: Added validation middleware to POST endpoint
- src/lib/validation.ts: Added TaskCreateSchema using Zod
THINGS I DIDN'T TOUCH (intentionally):
- src/routes/auth.ts: Has similar validation gap but out of scope
- src/middleware/error.ts: Error format could be improved (separate task)
POTENTIAL CONCERNS:
- The Zod schema is strict — rejects extra fields. Confirm this is desired.
- Added zod as a dependency (72KB gzipped) — already in package.json
This pattern catches wrong assumptions early and gives reviewers a clear map of the change. The "DIDN'T TOUCH" section is especially important — it shows you exercised scope discipline and didn't go on an unsolicited renovation.
Before every commit:
# 1. Check what you're about to commit
git diff --staged
# 2. Ensure no secrets
git diff --staged | grep -i "password\|secret\|api_key\|token"
# 3. Run tests
npm test
# 4. Run linting
npm run lint
# 5. Run type checking
npx tsc --noEmit
Automate this with git hooks:
// package.json (using lint-staged + husky)
{
"lint-staged": {
"*.{ts,tsx}": ["eslint --fix", "prettier --write"],
"*.{json,md}": ["prettier --write"]
}
}
package-lock.json, Prisma migrations)dist/, .next/), environment files (.env), or IDE config (.vscode/settings.json unless shared).gitignore that covers: node_modules/, dist/, .env, .env.local, *.pem# Find which commit introduced a bug
git bisect start
git bisect bad HEAD
git bisect good <known-good-commit>
# Git checkouts midpoints; run your test at each to narrow down
# View what changed recently
git log --oneline -20
git diff HEAD~5..HEAD -- src/
# Find who last changed a specific line
git blame src/services/task.ts
# Search commit messages for a keyword
git log --grep="validation" --oneline
| Rationalization | Reality |
|---|---|
| "I'll commit when the feature is done" | One giant commit is impossible to review, debug, or revert. Commit each slice. |
| "The message doesn't matter" | Messages are documentation. Future you (and future agents) will need to understand what changed and why. |
| "I'll squash it all later" | Squashing destroys the development narrative. Prefer clean incremental commits from the start. |
| "Branches add overhead" | Short-lived branches are free and prevent conflicting work from colliding. Long-lived branches are the problem — merge within 1-3 days. |
| "I'll split this change later" | Large changes are harder to review, riskier to deploy, and harder to revert. Split before submitting, not after. |
| "I don't need a .gitignore" | Until .env with production secrets gets committed. Set it up immediately. |
.gitignore in the projectnode_modules/, .env, or build artifactsFor every commit:
.gitignore covers standard exclusionsまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
日本語の概要は準備中です。原文の説明を表示しています。
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
日本語の概要は準備中です。原文の説明を表示しています。
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
日本語の概要は準備中です。原文の説明を表示しています。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
日本語の概要は準備中です。原文の説明を表示しています。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
日本語の概要は準備中です。原文の説明を表示しています。