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 when making an architectural decision, choosing between competing approaches, adding or changing a public API, shipping a user-facing behavior change, or repeatedly explaining the same thing. Captures the why — context, constraints, alternatives — as ADRs and project docs. Not for restating obvious code.
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.
Document decisions, not just code. The most valuable documentation captures the why — the context, constraints, and trade-offs that led to a decision. Code shows what was built; documentation explains why it was built this way and what alternatives were considered. This context is essential for future humans and agents working in the codebase.
When NOT to use: Don't document obvious code. Don't add comments that restate what the code already says. Don't write docs for throwaway prototypes.
ADRs capture the reasoning behind significant technical decisions. They're the highest-value documentation you can write.
Store ADRs in docs/decisions/ with sequential numbering:
# ADR-001: Use PostgreSQL for primary database
## Status
Accepted | Superseded by ADR-XXX | Deprecated
## Date
2025-01-15
## Context
We need a primary database for the task management application. Key requirements:
- Relational data model (users, tasks, teams with relationships)
- ACID transactions for task state changes
- Support for full-text search on task content
- Managed hosting available (for small team, limited ops capacity)
## Decision
Use PostgreSQL with Prisma ORM.
## Alternatives Considered
### MongoDB
- Pros: Flexible schema, easy to start with
- Cons: Our data is inherently relational; would need to manage relationships manually
- Rejected: Relational data in a document store leads to complex joins or data duplication
### SQLite
- Pros: Zero configuration, embedded, fast for reads
- Cons: Limited concurrent write support, no managed hosting for production
- Rejected: Not suitable for multi-user web application in production
### MySQL
- Pros: Mature, widely supported
- Cons: PostgreSQL has better JSON support, full-text search, and ecosystem tooling
- Rejected: PostgreSQL is the better fit for our feature requirements
## Consequences
- Prisma provides type-safe database access and migration management
- We can use PostgreSQL's full-text search instead of adding Elasticsearch
- Team needs PostgreSQL knowledge (standard skill, low risk)
- Hosting on managed service (Supabase, Neon, or RDS)
PROPOSED → ACCEPTED → (SUPERSEDED or DEPRECATED)
Comment the why, not the what:
// BAD: Restates the code
// Increment counter by 1
counter += 1;
// GOOD: Explains non-obvious intent
// Rate limit uses a sliding window — reset counter at window boundary,
// not on a fixed schedule, to prevent burst attacks at window edges
if (now - windowStart > WINDOW_SIZE_MS) {
counter = 0;
windowStart = now;
}
// Don't comment self-explanatory code
function calculateTotal(items: CartItem[]): number {
return items.reduce((sum, item) => sum + item.price * item.quantity, 0);
}
// Don't leave TODO comments for things you should just do now
// TODO: add error handling ← Just add it
// Don't leave commented-out code
// const oldImplementation = () => { ... } ← Delete it, git has history
/**
* IMPORTANT: This function must be called before the first render.
* If called after hydration, it causes a flash of unstyled content
* because the theme context isn't available during SSR.
*
* See ADR-003 for the full design rationale.
*/
export function initializeTheme(theme: Theme): void {
// ...
}
For public APIs (REST, GraphQL, library interfaces):
/**
* Creates a new task.
*
* @param input - Task creation data (title required, description optional)
* @returns The created task with server-generated ID and timestamps
* @throws {ValidationError} If title is empty or exceeds 200 characters
* @throws {AuthenticationError} If the user is not authenticated
*
* @example
* const task = await createTask({ title: 'Buy groceries' });
* console.log(task.id); // "task_abc123"
*/
export async function createTask(input: CreateTaskInput): Promise<Task> {
// ...
}
paths:
/api/tasks:
post:
summary: Create a task
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateTaskInput'
responses:
'201':
description: Task created
content:
application/json:
schema:
$ref: '#/components/schemas/Task'
'422':
description: Validation error
Every project should have a README that covers:
# Project Name
One-paragraph description of what this project does.
## Quick Start
1. Clone the repo
2. Install dependencies: `npm install`
3. Set up environment: `cp .env.example .env`
4. Run the dev server: `npm run dev`
## Commands
| Command | Description |
|---------|-------------|
| `npm run dev` | Start development server |
| `npm test` | Run tests |
| `npm run build` | Production build |
| `npm run lint` | Run linter |
## Architecture
Brief overview of the project structure and key design decisions.
Link to ADRs for details.
## Contributing
How to contribute, coding standards, PR process.
For shipped features:
# Changelog
## [1.2.0] - 2025-01-20
### Added
- Task sharing: users can share tasks with team members (#123)
- Email notifications for task assignments (#124)
### Fixed
- Duplicate tasks appearing when rapidly clicking create button (#125)
### Changed
- Task list now loads 50 items per page (was 20) for better UX (#126)
Special consideration for AI agent context:
| Rationalization | Reality |
|---|---|
| "The code is self-documenting" | Code shows what. It doesn't show why, what alternatives were rejected, or what constraints apply. |
| "We'll write docs when the API stabilizes" | APIs stabilize faster when you document them. The doc is the first test of the design. |
| "Nobody reads docs" | Agents do. Future engineers do. Your 3-months-later self does. |
| "ADRs are overhead" | A 10-minute ADR prevents a 2-hour debate about the same decision six months later. |
| "Comments get outdated" | Comments on why are stable. Comments on what get outdated — that's why you only write the former. |
After documenting:
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。