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概要と使いどころ
Generates individual Remotion scene components from visual direction. Input is visual/animation description for a specific scene. Output is SCENE_COMPONENT.md with complete TSX implementation. Use when implementing scenes or when asked to "create a scene component", "implement scene from spec", "build Scene1Intro".
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。
Professional content generation system with a GSD-style phased workflow, integrated SEO optimization (claude-seo), and anti-AI auditing (humanizer). USE THIS SKILL whenever the user asks to write, draft, create, generate, or produce ANY content — including blog posts, articles, LinkedIn posts, Facebook posts, Twitter/X tweets or threads, Instagram captions, email newsletters, email campaigns or sequences, landing pages, product pages, web pages, sales pages, sales funnels, case studies, testimonials, product descriptions, or SEO metadata. Also triggers on: "/writer:discuss", "/writer:plan", "/writer:execute", "/writer:verify", "/writer:ship", "/writer:next", "/writer:profile-create", "/writer:profile-view", "/writer:profile-edit", "/writer:status", "/writer:help", "/writer:update" — or any request to manage a writer profile or create marketing materials. ALWAYS use this skill even for quick, casual content requests like "write me a LinkedIn post about X" or "draft a tweet thread." The profile and phased workflow produce significantly better output than ad-hoc generation.
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Execute a Carmack Council plan task by task. Use when explicitly asked to implement a plan, do a "council implement", "carmack implement", "council build", or invoke /council-implement. Reads the output of /council-plan and builds each task sequentially, loading the relevant expert's reference document per task. Verifies after each task. Produces an implementation log for /council-review. Stack: Next.js App Router / React / TypeScript / tRPC / Prisma / Neon / Clerk.
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。
Generate structured software specifications for features, bug fixes, and products. Use when the user wants to create a spec, PRD, feature brief, requirements document, or when starting any new implementation that needs a specification first. Invoke via /spec-writer or when the user says "write a spec", "spec this out", "create a spec", "I need a spec for...", or describes a feature they want to build. Produces adaptive-complexity specs with Job Stories, Gherkin acceptance criteria, and three-tier boundaries. Output is a markdown file ready for agent execution or human review.
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。
Helps users set up and run MobiZen-GUI to perform mobile-use tasks — automating Android phone operations via natural language. Use when the user wants to control a phone, execute mobile-use tasks, install/configure MobiZen-GUI, deploy MobiZen-GUI-4B model, or customize the agent's input/output. Triggers on keywords like phone task, mobile-use, mobile automation, Android control, MobiZen, ADB, deploy model, run agent, configure 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。
Look at real hardware, screens, panels, and wiring on a desk or workbench through a camera, so Claude can SEE physical output that no unit test, log, or API can. Use whenever the user says "are you seeing this?", "olha isso", "look at this", "watch this", "can you see...", "check the camera", "look at the screen" / "look at the display", "is this wired right?", or "what's this part?"; asks to visually verify a rendered display, LCD, LED, or panel; wants a wiring, polarity, or voltage-rail check before power-on; or needs to confirm a font, layout, clipping, or on-screen value renders correctly instead of trusting green tests. Grabs the current camera frame(s) and reads them; supports a watch mode for an action in progress. Needs a snapshot-capable camera reachable over HTTP (Android IP Webcam app, Raspberry Pi camera-streamer, or any snapshot URL) set via CCE_CAM_URL.
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。
Fetch Cadmus application logs from Loki by run ID. Use when asked to look up logs for a specific run, debug a device session, or find log output for a given run 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。
Analyzes a project description and outputs a structured bid: scope, effort, tech risks, and optional pricing.
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 on any page build, redesign, or 'make it look better' request on a site that has (or needs) a saved Art Direction. Loads the direction before the first element is written, plans tokens in two passes against the direction's donts and the known AI-default aesthetics, builds with tokens preserved, checks the result with respira_check_design, and mints a live preview. Also the import lane for Claude Design output and other design-system documents.
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。
Rates any SKILL.md on a 0-100 scale across 10 dimensions with a SHIP / REWORK / SCRAP verdict. Evaluates trigger precision, instruction clarity, output predictability, edge case coverage, anti-hallucination guardrails, developer experience, composability, open-source readiness, wow factor, and real-world utility. No flattery — calibrated against Anthropic's own skill-creator rubric. Use this skill whenever someone says "score this skill", "rate my skill", "is this skill good", "skill review", "skill audit", "roast my SKILL.md", "grade this", "will this skill work", "evaluate my skill", "how good is this", or pastes a SKILL.md and asks for feedback. Also trigger when comparing two skills, benchmarking a skill collection, or asking "what's wrong with this skill" — even without the word "score".
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。
Display input/output args, return object and cost time of a Python method invocation in a live process. Use this to observe function behavior at runtime — see what arguments go in, what comes back, and how long it takes. This is the most frequently used diagnostic command.
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Bring Mycelium into a project that already has code. Detects that the repo predates the framework, asks before touching anything, then reads the codebase to draft what it CAN establish (delivery, solution shape) and — the actual point — names what it cannot (purpose, strategy, real user evidence). The output is a discovery backlog with a head start, never a filled canvas.
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 HTMLHint in .NET repositories that ship static HTML output or standalone frontend templates. Use when a repo needs a focused CLI lint gate for DOM structure, invalid attributes, and basic HTML correctness checks on static 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。
Use webhint in .NET repositories that ship browser-facing frontends. Use when a repo needs CLI audits for accessibility, performance, security headers, PWA signals, SEO, or runtime page quality against a served site or built frontend output.
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 the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team
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 whenever writing or updating a project-facing document — root CLAUDE.md, `.hedgehog/core-design.md`, specs, READMEs, or similar. Ensures the file reads as a clean, current, as-is snapshot rather than a log of edits or decisions. Applies on first generation and on every later revision, including "update," "rewrite," or "clean up" requests.
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。
Edits existing Stitch screens with text prompts — the iteration tool. Change colors, layout, content, or style without regenerating from scratch. Supports refinement loops via output_components suggestions.
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。
Iteratively build multi-page websites using Stitch. Reads next-prompt.md (the baton), generates the next page with Stitch MCP, integrates it into the site, then updates next-prompt.md to continue the loop. Works with stitch-design-md and stitch-ui-prompt-architect for consistent multi-page output.
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。
Reference for Claude Code's 6 Task Management tools — TaskCreate, TaskGet, TaskList, TaskUpdate (structured tracking) and TaskOutput, TaskStop (background execution). Covers tool parameters, status lifecycle, completion rules, dependency management, and conventions
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。
Convert Claude Code plugins into generic, platform-agnostic format. Supports full conversion (skills, agents, hooks), flatten mode (skills only — agents converted to skills, hooks absorbed), or nested mode (agents nested as pure markdown within parent skills, hooks absorbed). Full mode supports per-group or unified output layouts — unified merges all groups into a single directory organized by component type. Strips Claude Code-specific implementation details to produce clean markdown files preserving only the intent and instructions. Use when asked to "make this portable", "convert to generic format", "export plugin", "create universal skills", "strip platform dependencies", "make harness-agnostic", "decouple from Claude Code", "flatten to skills only", "nest agents in skills", or when the user wants their plugin content usable outside Claude Code. Also use when the user wants to share skills with teams using different agent frameworks.
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 verifying that a model in the imp inference engine produces coherent output without repetition loops, token-stuck states, or state corruption across turns or streams. Triggers on "degenerates", "check degeneration", "repetition loop", "own own own", "stuck token", "empty content", "multi-turn regression", "does it still work", "NIAH", and after enabling CUDA graphs / changing forward pass / MoE routing / KV cache or KV dtype / GDN state or scan / sparse attention / PDL / speculation (MTP, n-gram) / ragged prefill / batched-decode kernels (smallm, producer quantize) / FA2 softmax.
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 benchmarking, profiling, or A/B-testing CUDA kernels or end-to-end perf in the imp inference engine on RTX 5090 (sm_120), including refreshing tests/perf_baseline.json or publishing numbers to docs/BENCHMARKS.md and the README. Triggers on "benchmark kernel", "profile cuda", "ncu", "nsys", "kernel timing", "kernel sum", "occupancy", "bandwidth bound", "compute bound", "roofline", "perf baseline", "is this regression real", "decode dropped", "aggregate throughput", "two-image A/B", "prefill kernel A/B". Do NOT use for writing/optimizing kernel code (sm120-cuda-expert) or output-quality checks (check-degeneration).
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 building imp, running its test suite, checking CI status, or debugging build/test failures - "make build", "run the tests", "test-gpu", "verify-fast", GTEST_FILTER, Docker/CUDA toolchain, dependency bumps, "CI is red/blocked", "which gate failed", stale objects / segfault after a header edit, hook edits, docker-entrypoint env vars, determinism or perplexity checks. Do NOT use for benchmarking/profiling (benchmark-cuda) or output-quality batteries (check-degeneration).
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 working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).
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。