Mmcp.market

using-agent-skills skill

by addyosmani·addyosmani/agent-skills·100k stars·MIT

Discovers and invokes agent skills. Use when starting a session, or when you need to decide which skill or workflow applies to the piece of work at hand. This is the meta-skill that governs how all other skills are discovered and invoked.

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Install the using-agent-skills skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/addyosmani/agent-skills.git /tmp/agent-skills
mkdir -p ~/.claude/skills
cp -r /tmp/agent-skills/skills/using-agent-skills ~/.claude/skills/using-agent-skills
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Using Agent Skills

Overview

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.

Skill Discovery

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
    ├── No quality bar written down? ──→ constraint-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
    │   ├── Too complex? ─────────────→ code-simplification
    │   ├── Security concerns? ───────→ security-and-hardening
    │   └── Performance concerns? ────→ performance-optimization
    ├

Core Operating Behaviors

These behaviors apply at all times, across all skills. They are non-negotiable.

1. Surface Assumptions

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.

2. Manage Confusion Actively

When you encounter inconsistencies, conflicting requirements, or unclear specifications:

  1. STOP. Do not proceed with a guess.
  2. Name the specific confusion.
  3. Present the tradeoff or ask the clarifying question.
  4. Wait for resolution before continuing.

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?"

3. Push Back When Warranted

You are not a yes-machine. When an approach has clear problems:

  • Point out the issue directly
  • Explain the concrete downside (quantify when possible — "this adds ~200ms latency" not "this might be slower")
  • Propose an alternative
  • Accept the human's decision if they override with full information

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.

4. Enforce Simplicity

Your natural tendency is to overcomplicate. Actively resist it.

Before finishing any implementation, ask:

  • Can this be done in fewer lines?
  • Are these abstractions earning their complexity?
  • Would a staff engineer look at this and say "why didn't you just..."?

If you build 1000 lines and 100 would suffice, you have failed. Prefer the boring, obvious solution. Cleverness is expensive.

5. Maintain Scope Discipline

Touch only what you're asked to touch.

Do NOT:

  • Remove comments you don't understand
  • "Clean up" code orthogonal to the task
  • Refactor adjacent systems as a side effect
  • Delete code that seems unused without explicit approval
  • Add features not in the spec because they "seem useful"

Your job is surgical precision, not unsolicited renovation.

6. Verify, Don't Assume

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).

Per-skill verification is the local check. The project-wide bar that applies to every change, regardless of which skill is active, is the Definition of Done: tests pass, no regressions, behavior verified at runtime, docs updated. See ../../references/definition-of-done.md. It complements each task's acceptance criteria rather than replacing them.

Failure Modes to Avoid

These are the subtle errors that look like productivity but create problems:

  1. Making wrong assumptions without checking
  2. Not managing your own confusion — plowing ahead when lost
  3. Not surfacing inconsistencies you notice
  4. Not presenting tradeoffs on non-obvious decisions
  5. Being sycophantic ("Of course!") to approaches with clear problems
  6. Overcomplicating code and APIs
  7. Modifying code or comments orthogonal to the task
  8. Removing things you don't fully understand
  9. Building without a spec because "it's obvious"
  10. Skipping verification because "it looks right"

Skill Rules

  1. Check for an applicable skill before starting work. Skills encode processes that prevent common mistakes.
  1. Skills are workflows, not suggestions. Follow the steps in order. Don't skip verification steps.
  1. 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 → code-simplification → shipping-and-launch in sequence.
  1. When in doubt, start with a spec. If the task is non-trivial and there's no spec, begin with spec-driven-development.

Lifecycle Sequence

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.  observability-and-instrumentation → Instrument as you build (runs parallel with 7-9, not after)
9.  doubt-driven-development    → Cross-examine non-trivial decisions in-flight
10. test-driven-development     → Prove each slice works
11. code-review-and-quality     → Review before merge
12. code-simplification         → Reduce unnecessary complexity while preserving behavior
13. git-workflow-and-versioning → Clean commit history
14. documentation-and-adrs      → Document decisions
15. deprecation-and-migration   → Retire old systems and move users safely when needed
16. 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.

Quick Reference

More skills from addyosmani/agent-skills

  • Aapi-and-interface-designGuides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
  • Cbrowser-testing-with-devtoolsTests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
  • Aci-cd-and-automationAutomates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
  • Acode-review-and-qualityConducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.
  • Acode-simplificationSimplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
  • Aconstraint-driven-developmentEstablishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.
  • Acontext-engineeringOptimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
  • Adebugging-and-error-recoveryGuides systematic root-cause debugging. Use when tests fail, builds break, something that worked yesterday broke, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need to figure out what broke and why — a systematic approach to finding and fixing the root cause rather than guessing.
  • Adeprecation-and-migrationManages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when migrating a database schema in production, such as renaming or dropping a column without downtime (expand/contract). Use when deciding whether to maintain or sunset existing code.
  • Adocumentation-and-adrsRecords decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
  • Adoubt-driven-developmentSubjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
  • Afrontend-ui-engineeringBuilds production-quality, accessible, responsive user-facing UIs. Use when building or modifying interfaces and pages, creating components, implementing layouts, meeting WCAG accessibility requirements, managing state, or when the output needs to look and feel production-quality rather than AI-generated.

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