Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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 to create or clean up the CLAUDE.md (or AGENTS.md) file that tells a coding agent how to work in a repo — commands, conventions, architecture, and the traps. Trigger when onboarding an agent to a codebase, when the agent keeps making the same repo-specific mistake, or when the user asks for project instructions, agent rules, or a context file.
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。
A good project instruction file is the difference between an agent that guesses at your conventions and one that matches them on the first try. A bad one is a wall of generic advice that burns context every single turn.
Write instructions that are true, specific to this repo, and impossible to derive by looking around. Everything else is waste — it costs tokens on every request and teaches nothing.
Target length: under 100 lines. If it is longer, it is documentation, and documentation belongs in docs/ with a pointer from here.
Commands that are not obvious. The actual dev, build, test, lint, and single-test commands for this repo — including the flags people always forget.
npm run dev # port 3000, needs .env.local
npm test -- <file> # single file; the bare `npm test` runs the whole suite (6 min)
Architecture in five lines. Where the entry point is, where the data layer lives, what talks to what. Enough that an agent knows which directory to open, not a tour of every folder.
Conventions that a linter will not catch. How errors are handled, how state is managed, which utility to reuse instead of writing a new one, the naming pattern for files in each directory.
Traps. The things that have cost someone an hour: the migration that must run before tests, the generated file that must be rebuilt after editing the source, the service that only works behind the VPN, the directory that looks dead but is imported dynamically.
Hard rules. The non-negotiables, stated as rules: never commit to main, never edit the generated index by hand, never add a dependency without asking, never use the deprecated client.
src/lib/billing.ts".package.json scripts, CI config, and any existing contributor docs.git log for what changes most — that is where the conventions matter.# <Project>
<One sentence: what this is and who uses it.>
## Commands
<the handful that matter, with the gotcha flags>
## Architecture
<five lines, entry point first>
## Conventions
- <repo-specific rule> — see `path/to/exemplar.ts`
## Traps
- <the thing that wastes an hour>
## Rules
- Never <x>.
- Always <y>.
The file rots. Two triggers to update it: an agent made a repo-specific mistake that a line here would have prevented — add that line; or a stated instruction turned out to be false — fix it immediately, because one wrong instruction poisons trust in all of them.
Nested files work: a CLAUDE.md inside a package or app directory applies to work in that subtree. Use one when a monorepo's packages genuinely differ, rather than stuffing every package's quirks into the root file.
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
Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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。
Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
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 to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
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。
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
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。
Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.
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。
Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.
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。