2,353 件 ・ 関連度順
概要と使いどころ
Use when asked to run AST-based structural search, lint, or rewrite of code when regex is too fragile. Not for remote, credential, publish, deploy, or irreversible changes.
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 asked to design or change a public API, route, CLI flag, or module boundary. Not for remote, credential, publish, deploy, or irreversible changes.
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 repo needs agent setup, AGENTS.md added or made lean, CLAUDE.md audited, or agent instructions scored or pruned. Not for remote, credential, publish, deploy, or irreversible changes.
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 asked to audit comments in code files and propose structural replacements or deletions with per-candidate approval. Not for deterministic commented-out-code removal: use deslop.
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 non-trivial code needs a design, codebase design or architecture needs improving, or one module needs targeted interface narrowing, seams, or testability. Not for diagrams, deploy, or irreversible changes.
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 request names a working principle (subtract before you add, idempotent operations, never block on the human) or asks which principle applies. Not for running a repair: use strike-the-root.
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 human explicitly asks for a full repository agent-compatibility pass returning a scored report with prioritized fixes. Not for tasks that require source or remote-system changes.
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 human says "overhaul", "rebuild this subsystem", or "rewrite it from scratch". Not for thin-slice features: use incremental-implementation. Not for root-cause repair: use strike-the-root.
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 bug, failure, flake, regression, review finding, or ticket needs the core fixed so it cannot recur. Not for greenfield features: use tdd. Not for style-only review or typo-class one-liners.
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 asked to run /ios-build-fix to fix a failing iOS build, regenerate an Xcode project from project.yml, or correct UI behavior. Not for a clean rebuild: use ios-build-cleanup.
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 asked to optimize code, make a path faster, make this as fast as possible, reduce allocations, repair a regression, profile a target, grill every inefficiency, or run a subsystem or repo-wide performance campaign against a measured floor; when a performance requirement, slowness report, Core Web Vitals miss, or profiling evidence identifies a bottleneck; or for an "extremely optimize" performance campaign, optimizing suspected hot paths without waiting for benchmarks, or estimating hot and complexity-neutral cold paths while refusing complexity theater. Not for remote, credential, publish, deploy, or irreversible changes.
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 make the skills framework work in a new harness, IDE, or CLI. Not for remote, credential, publish, deploy, or irreversible changes.
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 user wants to define patterns the agent should not do. Don't use for remote, credential, publish, deploy, or irreversible changes.
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 asked to create an MCP server to integrate an API or service in Python or TypeScript. Not for remote, credential, publish, deploy, or irreversible changes.
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 an exact symbol, path, entrypoint, or line range can bound a focused code question or patch proposal under a fixed source budget. Not for source changes or broad repository exploration.
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。
Optimize a pydantic-ai agent's instructions, tool descriptions, output type, and signature inputs using the gepa CLI. Trigger when the user asks to "optimize this agent", "improve tool descriptions", iterate on prompts driven by eval failures, or otherwise improve a pydantic-ai agent against a dataset. Operates in the user's repo with full filesystem access — YOU are the reflection model; the gepa CLI handles minibatches, evaluation, and Pareto bookkeeping.
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。
Force `rust-embed` to re-embed assets from `$GRAFEMA_UI_DIST` (or any env-driven path) when cargo's incremental compilation skips the macro re-expansion. Use when: (1) you rebuilt the GUI bundle but the rust-server binary still serves the OLD bundle, (2) `cargo build --release` finishes in seconds (incremental hit) and `strings target/release/binary | grep <new-hash>` finds nothing, (3) any rust-embed pipeline where assets live outside the cargo source tree and are picked up via env var or symlink. Cargo only re-runs the proc macro when the rust file declaring `#[derive(RustEmbed)]` changes — env var changes alone don't trigger it.
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。
Etsy SEO optimization for existing and new listings. Auto-detects REWRITE (when user pastes a current title + tags + description) or CREATE (when user gives a short product context). Triggers on "rewrite this listing", "optimize my Etsy listing", "fix my title and tags", "create new listing", "make a new Etsy listing". Uses live Etsy autocomplete + competitor SERP scraping for evidence-driven keyword research. Enforces 2026 Etsy rules — tag ≤20 chars, primary keyword in first 40 chars, indexing spread across title/tags/attributes/description/hero alt, NLP-aware writing, trademark stoplist scan. When the user's problem isn't SEO (CTR, conversion, photos, price, saturated niche), it says so directly and routes to concrete next steps. Silently maintains a markdown listing database at ~/etsy-listings/ for cross-session memory on Claude/Cowork. Catches duplicate primary keywords across the user's own listings.
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 polished, code-driven Remotion motion explainers from scripts, narration, subtitles, product specifications, reference videos, UI recordings, diagrams, or abstract concepts. Use for product launches, AI demonstrations, UI interactions, algorithms, scientific principles, electrical systems, data flows, architecture, charts, equations, and concepts best expressed with React, SVG, Canvas, WebGL, or Three.js. Prioritize continuous spatial logic, visible cause and effect, precise interaction states, editable parameters, deterministic rendering, and evidence-backed visual QA.
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。
Before any material decision — code chunk, plan, strategy, design, scope cut, push to GitHub — convene a war-room. The session driver takes the CEO seat: frame the tradeoff, summon specialist seats from whatever agent roster the user has built, dispatch a cross-family voice via `ato dispatch` so priors actually disagree, decide. A failure-mode filter (wrong assumptions / overcomplexity / orthogonal edits / imperative-over-declarative — Karpathy's four are one good default, swap in your own) runs on every dispatch. Place in the v2.16 stack: war-rooms DECIDE before code starts; `ato-mission` EXECUTES the work between decisions (multi-step, goal-driven, persisted across days); `ato-review` VERIFIES the resulting commits. Use a war-room for the design verdict, hand the verdict to a Mission, review the merged result. Fires before: sending a code draft to the user as final, opening a PR, pushing to a remote-tracking branch, committing >50 LOC of behavior change, or delivering a plan or strategic recommendation as the final answer.
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。
Spec-driven development workflow. Interactive phase-by-phase confirmation from proposal to implementation. Trigger: 'spec-flow', 'spec mode', 'need a plan', 'structured development', 'write a spec', 'feature spec', 'technical spec', '需求文档', '技术方案', '任务拆解', '规格驱动', '写个方案', '做个规划', '结构化开发', 'plan this feature', 'break this down', 'design doc'. Creates .spec-flow/ directory with proposal, requirements, design, and tasks.
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 the failing test first, then the code that makes it pass.
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。
TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration 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。
Create branded 试界TryWorld AI-knowledge videos in the fixed "Paper Algorithm" (纸上算法) style with HyperFrames. Input is a Chinese voiceover script and optional images; output is a 16:9 horizontal video with Azure YunxiNeural (真·云希) voiceover, word-synced captions, ink/paper animations and unified transitions, an always-visible anti-counterfeit red seal, plus horizontal (4:3) and vertical (3:4) cover images and platform-optimized titles for Bilibili/Douyin/Xiaohongshu. Brand values are theme-driven (themes/paper-algorithm.json by default; custom brand themes supported — see references/theme-guide.md). Use when the user provides an AI 科普/教程/内容解读/知识分享 script and wants a TryWorld/试界 branded video, asks for the 纸上算法/Paper Algorithm style, wants a consistent script-to-video pipeline with covers and titles, or wants this pipeline with their own brand theme.
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。