Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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Use before writing code against a library, SDK, API, or framework whose current version you are not certain of — especially fast-moving ones. Trigger when an import fails, a method does not exist, a config key is rejected, a deprecation warning appears, or the user says the code was written against an old version.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Training data has a cutoff; libraries do not. Most "the AI hallucinated an API" bugs are really the model writing correct code for a version that shipped two years ago. This skill checks reality first.
Before writing non-trivial code against a dependency, establish two facts: which version this project actually has, and what that version's API looks like. In that order.
The installed version beats the latest version and beats your memory. Read it from the project:
cat package.json | grep -A30 '"dependencies"'
npm ls <pkg> --depth=0 2>/dev/null
pip show <pkg> 2>/dev/null | head -3
cat requirements.txt pyproject.toml 2>/dev/null | grep -i <pkg>
The most reliable documentation is the code on disk. It cannot be out of date, because it is what will run.
ls node_modules/<pkg>/dist/*.d.ts
grep -rn "export function <name>\|export declare" node_modules/<pkg>/dist/index.d.ts | head -20
python -c "import <pkg>, inspect; print(inspect.signature(<pkg>.<fn>))"
For a TypeScript project, the .d.ts file answers the question definitively. Read it before searching the web.
When the source is unreadable or you need usage patterns rather than signatures:
Blog posts and forum answers are the last resort and always carry a date. A 2023 tutorial for a library that had a major release last year is a trap.
For anything non-obvious, run the smallest possible check rather than trusting the read:
node -e "const x=require('<pkg>'); console.log(Object.keys(x).slice(0,30))"
npx tsc --noEmit 2>&1 | head -20
Type-check output is the cheapest proof that an API call exists.
Verify these every time; they move fastest and break most: AI SDKs and model identifiers, auth libraries, ORMs and database clients, build tooling and bundler config, meta-framework routing and data-fetching conventions, payment SDKs. For model names, pricing, and parameters specifically, check the provider's current model list rather than recalling one.
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Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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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.
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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.
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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.
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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.
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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.
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