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概要と使いどころ
Generate structured research briefs from RSS feeds and web sources on any topic. Synthesizes multiple sources into actionable analysis with key findings, data points, expert perspectives, and content angles.
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。
Conversion Rate Optimization auditing for landing pages, signup flows, checkout funnels, forms, and CTAs. Identifies friction points, runs heuristic evaluations, produces prioritized recommendations using ICE/PIE frameworks. Use when the user asks about conversion optimization, funnel analysis, landing page audits, form optimization, CTA testing, or checkout improvement.
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。
Extract and analyze competitor advertising from public ad libraries (Facebook Ad Library, Google Ads Transparency Center, TikTok, LinkedIn). Identifies messaging patterns, creative formats, pain points targeted, and positioning gaps. Use for competitive intelligence, campaign planning, and creative inspiration.
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。
Excalibur.js is a TypeScript-first 2D game engine for the browser with actors, scenes, collision physics, animation, sound, input and a Tiled map plugin. Use when the user wants to build or debug a browser game with Excalibur, load Tiled maps, animate sprite sheets, handle keyboard or pointer input, or manage scenes and cameras.
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。
Rebuilds an existing website as a clean new codebase that looks and behaves like the original: captures pages, breakpoints, design tokens, assets and interaction states with a browser tool, plans the build, rebuilds section by section and proves each one against the capture with a pixel diff. Use when the user says "clone this website", "rebuild my site in Next.js or Astro", "recreate this page pixel-perfect", "move my Webflow or WordPress site to code" or "copy this layout". Full copies are only for sites the user owns or is authorized to copy; for anyone else's site it borrows the layout ideas and never the brand, content or sign-in pages.
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。
Test web application security with Burp Suite. Use when a user asks to intercept HTTP traffic, test for web vulnerabilities, fuzz API endpoints, analyze authentication flows, or perform manual web application pentesting.
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。
Cerebras Inference is a hosted LLM API that runs open models on Cerebras wafer-scale chips at thousands of tokens per second, through an OpenAI-compatible endpoint. Use when a user wants the lowest-latency chat, code completion or agent loop, asks how to call the Cerebras API or SDK, needs streaming, tool calling, strict JSON schema output or reasoning control, or hits a "model not found" error from a retired Cerebras model ID.
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。
Aider is an open-source terminal AI pair programmer that edits files in your git repository with an LLM and commits each change. Use when a user asks to run Aider, let an AI refactor or fix code from the command line, script Aider with --message, auto-run lint and tests after edits, or point Aider at Claude, GPT, Gemini, DeepSeek or a local model.
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。
GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully. 2025 lesson: GraphQL isn't always the answer. For simple CRUD, REST is simpler. For high-performance public APIs, REST with caching wins. Use GraphQL when you have complex data relationships and diverse client needs. Use when "graphql, graphql schema, graphql resolver, apollo server, apollo client, graphql federation, dataloader, graphql codegen, graphql query, graphql mutation, graphql, api, apollo, schema, resolvers, dataloader, federation, typescript" mentioned.
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。
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when "langgraph, langchain agent, stateful agent, agent graph, react agent, agent workflow, multi-step agent, langgraph, langchain, agents, state-machine, workflow, graph, ai-agents, orchestration" mentioned.
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 training models across multiple GPUs or nodes, handling large models that don't fit in memory, or optimizing training throughput - covers DDP, FSDP, DeepSpeed ZeRO, model/data parallelism, and gradient checkpointingUse when ", " mentioned.
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。
Design and implement discrete event simulations (DES) for systems where state changes occur at discrete time points: queues, manufacturing, logistics, networks. Use when "discrete event, DES simulation, queuing system, queue model, manufacturing simulation, process simulation, SimPy, event-driven simulation, " mentioned.
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。
World-class copywriting expertise combining the persuasive clarity of David Ogilvy, the conversational warmth of Ann Handley, and the conversion science of modern growth marketers. Copywriting is where brand voice becomes words that move people. Great copy doesn't just communicate—it persuades, connects, and converts. The best copywriters understand that every word earns its place, that benefits beat features, that clarity trumps cleverness, and that the reader's problem is the only starting point that matters. Use when "copywriting, write copy, headlines, taglines, email copy, ad copy, landing page copy, product copy, UX writing, CTAs, value proposition, microcopy, sales copy, conversion copy, writing, copy, headlines, conversion, persuasion, messaging, UX-writing, emails" mentioned.
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。
The art and science of narrative-driven brand communication. This skill transforms brand messages into compelling stories that connect emotionally, build memory, and drive action. In a world of infinite content, story is the only thing that cuts through. Great brands don't sell products—they tell stories. Apple tells the story of creative rebels. Nike tells the story of human potential. Patagonia tells the story of environmental stewardship. This skill teaches you to find, craft, and tell your brand's story across every touchpoint. AI amplifies storytelling capability—generating variations, adapting across channels, maintaining consistency—but the human insight that identifies the true story remains essential. This skill bridges narrative craft with AI execution. Use when "story, storytelling, narrative, brand story, origin story, hero journey, emotional connection, customer story, testimonial, case study, brand film, about us, storytelling, narrative, brand-story, emotional, hero-journey, content" mentioned.
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。
Expert in Claude Code hooks - user-defined shell commands that execute at specific points in Claude Code's lifecycle. Provides guaranteed automation that doesn't rely on the LLM "remembering" to do something. Essential for enterprise workflows, code quality enforcement, and deterministic behavior in agentic coding. Use when "claude code hooks, automate claude, block tool use, pre tool use, post tool use, session start hook, claude lifecycle, claude-code, automation, hooks, lifecycle, cli, workflow, devtools" mentioned.
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。
The craft of creating and maintaining cohesive brand identity systems. Branding translates brand strategy into tangible visual and verbal identity—logos, color systems, typography, imagery, and voice guidelines that work together to make a brand recognizable and memorable. This skill covers logo design, visual identity systems, brand guidelines, naming, verbal identity, and brand application across touchpoints. Great branding is invisible when done right—it feels inevitable, as if the brand couldn't have looked any other way. Use when "logo, branding, brand identity, brand guidelines, visual identity, color palette, typography, brand book, naming, rebrand, brand refresh, brand system, branding, identity, logo, visual-design, guidelines, naming, typography, color" mentioned.
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。
Expert in designing and implementing visceral, satisfying combat systems. Masters hitbox/hurtbox design, frame data, combo systems, enemy archetypes, damage feedback, and the invisible craft that makes players feel powerful. Draws from fighting games, character action games (DMC, Bayonetta), and Souls-like design to create combat that is readable, responsive, and endlessly replayable. Use when "combat system, combat design, hitbox, hurtbox, frame data, hitstop, screen shake, input buffer, coyote time, i-frames, invincibility frames, combo system, attack cancel, recovery frames, punishment window, souls-like combat, action game combat, fighting game, damage feedback, enemy design, boss design, attack telegraph, parry system, stamina system, poise system, weapon feel, game feel combat, melee combat, combat juice, combat, action-game, fighting-game, hitbox, frame-data, game-feel, souls-like, character-action, melee, enemy-design, boss-design, combo, parry, i-frames" mentioned.
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。
Patterns for designing and analyzing clinical trials, including survival analysis, endpoint selection, sample size calculation, interim analyses, and regulatory considerations. Covers FDA/EMA guidelines and modern adaptive designs. Use when ", " mentioned.
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。
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% by step 10. Build for reliability first, autonomy second. 2025 lesson: The winners are constrained, domain-specific agents with clear boundaries, not "autonomous everything." Treat AI outputs as proposals, not truth. Use when "autonomous agent, autogpt, babyagi, self-prompting, goal decomposition, react pattern, agent loop, self-correcting agent, reflection agent, langgraph, agentic ai, agent planning, autonomous, agents, langgraph, react, planning, reflection, guardrails, reliability, checkpointing" mentioned.
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。
API design specialist for REST, GraphQL, gRPC, versioning strategies, and developer experienceUse when "api design, rest, graphql, grpc, openapi, swagger, versioning, pagination, rate limiting, endpoint, api, rest, graphql, grpc, openapi, swagger, versioning, pagination, rate-limiting, ml-memory" mentioned.
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 keywords competitors rank for that you don't, via the DataForSEO Labs domain_intersection endpoint. Surfaces the highest-leverage content opportunities sorted by search volume and the competitor's ranking position, with cross-competitor consensus signals.
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 SEO audit powered by the DataForSEO API. Orchestrates 5 specialist subagents (keywords, technical, competitors, content, backlinks) hitting DataForSEO Keywords Data, SERP, On-Page, Backlinks, and Labs endpoints in parallel, then produces a composite SEO Score (0-100) with prioritized action plan and audit JSON ready for PDF export.
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。
Performs a fast 6-point quality check for technical documents (specs, design docs, READMEs). Use after editing any specification or design document.
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。
Synthesize the single strongest EVIDENCE-BOUND reviewer case to reject a paper, built ONLY from the evidence ledger (claims.json) + the other auditors' confirmed findings — never free-floating LLM critique. Two fresh cross-model codex threads: an attack writes the ~200-word rejection paragraph (every accusation tagged to an existing claim_id/finding_id), a defense decomposes it and rules each point against the anchored evidence. MEMO-ONLY: emits adversarial-case-builder.memo.md (fed to the adjudicator via --memo) and carries NO verdict weight — tools/adjudicate_findings.py lists it in ZERO_WEIGHT_SKILLS and caps it at info. Honest-null allowed (the paper may survive). Run LAST. Detect-only. Adapted from ARIS kill-argument. Triggers: "adversarial case", "strongest objection", "rejection memo", "kill argument", "最强拒稿点".
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。