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概要と使いどころ
Translate a vague request or GitHub issue into a concrete, testable spec using five structured elements (problem, scope, acceptance criteria, edge cases, success criterion) before writing any code. Prevents scope creep, PR churn, and mid-implementation pivots.
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。
Transforms a rough idea into a detailed design document with implementation plan. Follows Prompt-Driven Development — iterative requirements clarification, research, design, and planning.
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。
Create QA checklists for verifying design implementation accuracy.
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。
Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.
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。
Find documentation and repository evidence for library behavior, API contracts, error messages, and known bugs. Use when a programming question needs current public documentation, issues, pull requests, or implementation examples.
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。
Push interfaces past conventional limits with technically ambitious implementations. Whether that's a shader, a 60fps virtual table, spring physics on a dialog, or scroll-driven reveals — make users ask "how did they do that?"
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。
Claim one live GitHub queue item, implement it end to end, run fail-closed gates and independent verification, then open a draft PR. Use for one ready-to-implement issue or the implementation routine.
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。
When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.
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。
Build an animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations.
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。
Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.
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。
Discover and reduce task unknowns — blindspots, missing context, and unknown unknowns — before committing to a plan, implementation, review, or merge.
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。
Implements real-time WebSocket communication with connection management, room-based messaging, and horizontal scaling. Use when building chat systems, live notifications, collaborative tools, or real-time dashboards.
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。
Adaptive interview-driven spec generation. Use when converting rough plans into comprehensive specifications, needing structured requirements gathering, or transforming ideas into implementation-ready documentation.
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。
OAuth 2.0 and OpenID Connect authentication with secure flows. Use for third-party integrations, SSO systems, token-based API access, or encountering authorization code flow, PKCE, token refresh, scope management errors.
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。
Builds GraphQL APIs with schema design, resolvers, error handling, and performance optimization using Apollo or Graphene. Use when creating flexible query APIs, migrating from REST, or implementing real-time subscriptions.
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 for mock functions in Bun tests, spyOn, mock.module, implementations, and test doubles.
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。
Full workflow to add support for a new Eufy Security device type (cameras, locks, sensors, and other devices) across eufy-security-client and homebridge-eufy-security. Covers exploration, implementation, build verification, and git/PR creation.
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。
Judgment rules for locating the correct boundary of a requested change: staying inert outside it while completing every required site inside it. Use when scope is ambiguous, a diff touches neighboring surfaces, required dependent edits are unclear, or a proposed compatibility layer, migration, fallback, flag, abstraction, or parallel implementation may exceed the request.
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。
When handing work to the Codex CLI earns its cost, and how to size the run: second-model review, bounded implementation hand-offs, sandbox permissions, model and reasoning effort. Use when the user asks for Codex or `codex exec`, when a change is complex or high-stakes enough that an independent reviewer would change the outcome, or when a delegated run needs its model, effort, or permissions chosen. For agents other than Codex itself.
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。
Guide a user from an unclear idea to an actionable plan through the agent harness's native ask tool and clickable choices. Use when the user wants a guided requirements interview, step-by-step questions, help deciding what to build, or a button-led path from goals to scope, solution, and technology choices. Do not turn an ordinary implementation request or a single clarification into an interview.
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。
Delegate bounded investigation, review, or implementation tasks to Antigravity CLI from a supervising agent. Includes a background client for task progress, follow-up prompts, conversation recovery, cancellation, and visible failures.
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 the user asks to run or continue an autonomous build: turn a goal into an approved plan, dispatch implementation and review agents, and finish with one pull request. The Lead is a provider-neutral orchestrator that makes decisions but never writes code, edits files, runs commands, or reviews its own work.
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 a task may benefit from a bounded subagent for implementation, large-codebase discovery at task start, independent review, requested or pre-commit code simplification, or expert work on complex decisions, modeling, automation, or repeated failures. The main agent chooses whether to delegate and accepts the result. Do not use for simple questions or short work with no meaningful review or delegation.
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。
Lightweight standalone design spec for AI coding agents: codebase scan → bounded clarify pass (3–5 questions, not a grill) → reviewed design doc written to docs/plans/ → independent scored review → stop. No task board, no build. Use when you want a spec to discuss, hand off, or review before committing to implementation. Chains into absolute-work when ready to build. Triggers on "absolute spec", "write a spec", "spec out this feature", "draft a design doc", "I want a spec to hand off / review, don't build it yet".
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。