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概要と使いどころ
Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.
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。
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
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。
Complete Claude Code productivity system — project setup, prompting patterns, sub-agent orchestration, context management, debugging, refactoring, TDD, and shipping 10X faster. Zero scripts needed.
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, build, test, document, and secure production-grade APIs. Covers the full lifecycle from schema design through deployment, monitoring, and versioning. Use when designing new APIs, reviewing existing ones, generating OpenAPI specs, building test suites, or debugging production issues.
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。
End-to-end MegaETH development playbook (Feb 2026). Covers wallet operations, token swaps (Kyber Network), eth_sendRawTransactionSync (EIP-7966) for instant receipts, JSON-RPC batching, real-time mini-block subscriptions, storage-aware contract patterns (Solady RedBlackTreeLib), MegaEVM gas model, WebSocket keepalive, bridging from Ethereum, and debugging with mega-evme. Use when building on MegaETH, managing wallets, sending transactions, or deploying contracts.
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。
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
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。
Requires OFOX_API_KEY — create one at https://app.ofox.ai. Shared execution layer for the Ofox video generation API (api.ofox.ai) — creates a video job, polls it to completion, downloads the finished mp4 from a persistent CDN URL, and reports the real cost. This is a library skill, not a standalone user-facing one — it is invoked by scenario skills such as seedance-short-drama, seedance-ad-creative, and seedance-product-video, which build model/prompt/resolution choices for a specific use case and then call into this skill's script rather than re-implementing the API calls. Load this skill directly only when a user explicitly names the Ofox video API, asks to call it with specific low-level parameters, or asks to debug/resume a stuck or failed Ofox video job by job id — for a plain scenario request ("make me a short drama scene", "generate a cinematic ad clip"), use the relevant scenario skill instead, which itself depends on this one.
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。
Requires OFOX_API_KEY — create one at https://app.ofox.ai. Shared execution layer for the Ofox image API (api.ofox.ai) — validates parameters client-side, sends one synchronous request, base64-decodes the result, saves it to a file, and reports the real usage token counts and the computed dollar cost. Does both text-to-image (generate) and editing an existing image you supply as a local file (edit — change the background, recolour an element, alter a product photo, while leaving the rest of the picture intact). This is a library skill, not a standalone user-facing one — it is meant to be invoked by scenario skills that build model/prompt/size choices for a specific use case and then call into this skill's script rather than re-implementing the API calls — image-edit owns "change this image so that...", product-image owns a set of product images to choose between, and seedance-anime-drama owns character images for a video pipeline. Load this skill directly only when a user explicitly names the Ofox image API, asks to call it with specific low-level parameters, asks to debug a failed Ofox image request, or wants a plain "generate an image of..." from text — which is the one common case no scenario skill covers.
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。
Captures executable contracts and coding conventions into .trellis/spec/ documents. Use when learning something valuable from debugging, implementing, or discussion that should be preserved for future sessions.
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 error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.
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。
Apply rapport-based elicitation to resistant or semi-cooperative humans and agents. Use when coercive prompting or brittle handoffs damage cooperation. NOT for routine cooperative tasks, pure technical debugging, or already reliable exchanges.
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。
Apply rapport-based elicitation to resistant or semi-cooperative humans and agents. Use when coercive prompting or brittle handoffs damage cooperation. NOT for routine cooperative tasks, pure technical debugging, or already reliable exchanges.
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。
Analyze hierarchical DAG-like systems by separating undirected substrate from ordering metadata, then classifying diamonds, mixers, shortcuts, and hidden cycle structure. Use for workflow architecture, citation or genealogy DAG comparison, and information-flow diagnosis. NOT for ordinary cycle detection in arbitrary graphs, one-node runtime debugging, or systems with no real ordering constraint.
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。
Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).
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 applying Cloudflare D1 migrations, fighting Supabase migration history vs SQL execution, choosing direct psql over CLI, designing idempotent migrations, debugging schema drift between local and remote, or recovering after a half-applied migration. Triggers: supabase migration repair instructions appearing, table missing after "applied" status, "Tenant or user not found" when running psql, --remote vs --local D1 confusion, NOT NULL on a populated column, foreign key constraint failures, drift between staging and prod schemas. NOT for Mongo/document migrations, ORM-managed migrations specifically (Prisma/Drizzle have their own conventions), or pure data backfills.
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。
Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.
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, debug, optimize, and deploy ComfyUI workflows for diffusion image, video, and audio generation. Activate on: ComfyUI workflow, ComfyUI custom node, ComfyUI API, ComfyUI Manager, KSampler, FLUX in ComfyUI, Wan 2.2 ComfyUI, Hunyuan video ComfyUI, LTX video ComfyUI, IPAdapter, ControlNet ComfyUI, Kijai wrapper, ComfyDeploy, RunComfy, ComfyUI security, GGUF quantization, TeaCache, Nunchaku, ACE-Step ComfyUI, F5-TTS ComfyUI, subgraphs ComfyUI. NOT for: A1111/Forge/Invoke (different UIs), training pipelines from scratch, non-diffusion ML models, or general image-API integrations (use generative-video-2026 / generative-music-audio / media-gen-deployment).
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 designing or fixing a Content Security Policy on a real site, choosing between nonce-based and hash-based CSP, adding strict-dynamic, debugging "Refused to execute inline script" errors, deploying CSP in report-only mode first, configuring report-to / report-uri, or auditing an existing policy for unsafe-inline / unsafe-eval / wildcards. Triggers: "CSP blocks legitimate inline script", strict-dynamic, nonce-{RANDOM}, sha256-{HASH}, object-src none, base-uri none, frame-ancestors, Trusted Types, X-Content-Security-Policy obsolete, report-only vs enforced. NOT for general HTTP security headers (HSTS, COOP/COEP), Trusted Types deep dive, CORS configuration, or building a WAF.
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。
Architecture-level decisions for putting a CDN in front of a web app's static assets, API responses, and file/media delivery: provider selection (hyperscaler vs. specialist $/GB), signed-URL / tokenized access for gating private content at the edge, cache invalidation strategy (versioned URLs vs. purge APIs), origin shield / tiered caching for high-miss-rate content, and CDN-layer geo-restriction. Use when deciding which CDN to put in front of a new or growing service, when private/paywalled files need edge delivery without an origin round-trip per request, or when purge/invalidation behavior is being designed rather than debugged. NOT for HTTP cache-control header syntax, Vary, stale-while-revalidate, or surrogate-key purge mechanics (see `cdn-cache-control-headers`); NOT for Cloudflare-specific product configuration once Cloudflare is already chosen (see `cloudflare`); NOT for video-specific transcoding, adaptive bitrate ladders, or streaming-protocol packaging (see `managed-video-streaming-pipeline`).
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。
Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.
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。
Implement an executable BDI agent cycle with events, context-guarded plans, intention stacks, selection functions, and belief revision. Use when designing or debugging AgentSpeak-style runtimes or concrete BDI program semantics. NOT for high-level BDI adoption, organizational modeling, norms, or hypertree team 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。
Implement a structured error class hierarchy with actionable messages, proper exit codes, debug mode via env var, and bug report hints on unexpected errors. Generic pattern for any CLI tool or Node.js application.
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。
ScepticAgent internal architecture reference. Use whenever the user asks how the extension works, wants to add a new AI provider, add a new highlight category, debug communication between components, understand the agent loop or streaming, or work with provider routing and the Gemini CORS proxy.
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。