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 unsure which engineering-workflow skill applies to the task at hand. Routes from development phase — idea, spec, plan, implement, test, review, ship — to the right skill, and shows how they chain together across a feature or bugfix.
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.
Agent Skills is a collection of engineering workflow skills organized by development phase. Each skill encodes a specific process that senior engineers follow. This meta-skill helps you discover and apply the right skill for your current task.
When a task arrives, identify the development phase and apply the corresponding skill:
Task arrives
│
├── Don't know what you want yet? ──────→ interview-me
├── Have a rough concept, need variants? → idea-refine
├── New project/feature/change? ──→ spec-driven-development
├── Have a spec, need tasks? ──────→ planning-and-task-breakdown
├── Implementing code? ────────────→ incremental-implementation
│ ├── UI work? ─────────────────→ frontend-ui-engineering
│ ├── API work? ────────────────→ api-and-interface-design
│ ├── Need better context? ─────→ context-engineering
│ ├── Need doc-verified code? ───→ source-driven-development
│ └── Stakes high / unfamiliar code? ──→ doubt-driven-development
├── Writing/running tests? ────────→ test-driven-development
│ └── Browser-based? ───────────→ browser-testing-with-devtools
├── Something broke? ──────────────→ debugging-and-error-recovery
├── Reviewing code? ───────────────→ code-review-and-quality
│ ├── Security concerns? ───────→ security-and-hardening
│ └── Performance concerns? ────→ performance-optimization
├── Committing/branching? ─────────→ git-workflow-and-versioning
├── CI/CD pipeline work? ──────────→ ci-cd-and-automation
├── Writing docs/ADRs? ───────────→ documentation-and-adrs
└── Deploying/launching? ─────────→ shipping-and-launch
These behaviors apply at all times, across all skills. They are non-negotiable.
Before implementing anything non-trivial, explicitly state your assumptions:
ASSUMPTIONS I'M MAKING:
1. [assumption about requirements]
2. [assumption about architecture]
3. [assumption about scope]
→ Correct me now or I'll proceed with these.
Don't silently fill in ambiguous requirements. The most common failure mode is making wrong assumptions and running with them unchecked. Surface uncertainty early — it's cheaper than rework.
When you encounter inconsistencies, conflicting requirements, or unclear specifications:
Bad: Silently picking one interpretation and hoping it's right. Good: "I see X in the spec but Y in the existing code. Which takes precedence?"
You are not a yes-machine. When an approach has clear problems:
Sycophancy is a failure mode. "Of course!" followed by implementing a bad idea helps no one. Honest technical disagreement is more valuable than false agreement.
Your natural tendency is to overcomplicate. Actively resist it.
Before finishing any implementation, ask:
If you build 1000 lines and 100 would suffice, you have failed. Prefer the boring, obvious solution. Cleverness is expensive.
Touch only what you're asked to touch.
Do NOT:
Your job is surgical precision, not unsolicited renovation.
Every skill includes a verification step. A task is not complete until verification passes. "Seems right" is never sufficient — there must be evidence (passing tests, build output, runtime data).
These are the subtle errors that look like productivity but create problems:
Check for an applicable skill before starting work. Skills encode processes that prevent common mistakes.
Skills are workflows, not suggestions. Follow the steps in order. Don't skip verification steps.
Multiple skills can apply. A feature implementation might involve idea-refine → spec-driven-development → planning-and-task-breakdown → incremental-implementation → test-driven-development → code-review-and-quality → shipping-and-launch in sequence.
When in doubt, start with a spec. If the task is non-trivial and there's no spec, begin with spec-driven-development.
For a complete feature, the typical skill sequence is:
1. interview-me → Extract what the user actually wants
2. idea-refine → Refine vague ideas
3. spec-driven-development → Define what we're building
4. planning-and-task-breakdown → Break into verifiable chunks
5. context-engineering → Load the right context
6. source-driven-development → Verify against official docs
7. incremental-implementation → Build slice by slice
8. doubt-driven-development → Cross-examine non-trivial decisions in-flight
9. test-driven-development → Prove each slice works
10. code-review-and-quality → Review before merge
11. git-workflow-and-versioning → Clean commit history
12. documentation-and-adrs → Document decisions
13. shipping-and-launch → Deploy safely
Not every task needs every skill. A bug fix might only need: debugging-and-error-recovery → test-driven-development → code-review-and-quality.
| Phase | Skill | One-Line Summary |
|---|---|---|
| Define | interview-me | Surface what the user actually wants before any plan, spec, or code exists |
| Define | idea-refine | Refine ideas through structured divergent and convergent thinking |
| Define | spec-driven-development | Requirements and acceptance criteria before code |
| Plan | planning-and-task-breakdown | Decompose into small, verifiable tasks |
| Build | incremental-implementation | Thin vertical slices, test each before expanding |
| Build | source-driven-development | Verify against official docs before implementing |
| Build | doubt-driven-development | Adversarial fresh-context review of every non-trivial decision |
| Build | context-engineering | Right context at the right time |
| Build | frontend-ui-engineering | Production-quality UI with accessibility |
| Build | api-and-interface-design | Stable interfaces with clear contracts |
| Verify | test-driven-development | Failing test first, then make it pass |
| Verify | browser-testing-with-devtools | Chrome DevTools MCP for runtime verification |
| Verify | debugging-and-error-recovery | Reproduce → localize → fix → guard |
| Review | code-review-and-quality | Five-axis review with quality gates |
| Review | security-and-hardening | OWASP prevention, input validation, least privilege |
| Review | performance-optimization | Measure first, optimize only what matters |
| Ship | git-workflow-and-versioning | Atomic commits, clean history |
| Ship | ci-cd-and-automation | Automated quality gates on every change |
| Ship | documentation-and-adrs | Document the why, not just the what |
| Ship | shipping-and-launch | Pre-launch checklist, monitoring, rollback plan |
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。