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概要と使いどころ
Analyzes apparel demand prediction systems for trend forecasting, size curve optimization, color and style analytics, sell-through rate tracking, and markdown optimization following CPFR collaborative planning and GTIN product identification standards..
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。
Review custom components and layouts against shadcn design patterns, visual style conventions (Vega, Nova, Maia, Lyra, Mira), composition rules, design token usage, and Radix/Base UI composition patterns. Use PROACTIVELY after writing or modifying any custom UI component, page layout, or variant of a shadcn component. Use when the user says "review this component", "check my spacing", "does this follow shadcn patterns", "audit this layout", "is this shadcn-idiomatic", or shares a component for feedback. Catches spacing drift, hardcoded colors, missing data-slot attributes, inconsistent theme application, and composition anti-patterns that shipping-fast-with-AI tools often miss.
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Document a design system component. Use when the user says "design system docs", "document this for the design system", "add this to the design system", "design token", "component library docs", "style guide", "design system entry", or wants to formally document a pattern, component, or token for team-wide use - even if they don't explicitly say "design system".
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。
Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.
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Browse, filter, and explore a curated library of 2,500+ AI prompts organized by 19 categories, 17 models, and 4 output types. View stats, discover trending styles, and export prompt collections. Use when user says "prompt library", "browse prompts", "show categories", "list prompts", "prompt collection", "explore prompts", or "what prompts do we have".
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。
Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and evidence-backed explanations. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".
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。
Audit and score blog posts on a 5-category 100-point scoring system covering content quality, SEO optimization, E-E-A-T signals, technical elements, and AI citation readiness. Includes advisory editorial style diagnostics (sentence-length variation, configured phrase lists, vocabulary sampling) that never infer authorship or affect scoring. Supports export formats (markdown, JSON, table) and batch analysis with sorting. Generates prioritized recommendations (Critical/High/Medium/Low) with specific fixes. Works with any format (MDX, markdown, HTML, URL). Use when user says "analyze blog", "audit blog", "blog score", "check blog quality", "blog review", "rate this blog", "blog health check".
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 and manage writing personas with NNGroup 4-dimension tone framework (Funny-Serious, Formal-Casual, Respectful-Irreverent, Enthusiastic-Matter-of-fact). Personas define readability targets, sentence length distribution, vocabulary tier, contraction frequency, and summary box label. Used by blog-write and blog-rewrite to enforce consistent voice. Use when user says "persona", "voice", "tone", "writing style", "brand voice", "create persona", "use persona".
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 gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat Channels), or asks to learn visual design patterns from a reference video/image. Trigger when the user mentions creating a knowledge video, narrated explainer, video podcast, or animated infographic-style video from a topic — even if they don't say "video podcast" explicitly. Also trigger when the user wants to regenerate, re-render, rebuild, update, or iterate on a narrated video this skill already produced — e.g. they edited the script/prompt, changed the visuals, or swapped the background music and want the final video remade (reuse the existing videos/{name}/ directory, never start a new project). Do NOT trigger for generic video editing, trimming, format conversion, color grading, or non-narrative video tasks. Produces 4K video via research → script → TTS → Remotion → MP4 + BGM.
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。
Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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。
Obsidian Claw is an ontology-building skill that transforms chaotic notes, raw ideas, voice dumps, and meeting transcripts into a structured, interlinked knowledge base inside Obsidian. Use this skill whenever the user wants to: add new notes to their Obsidian vault and auto-link them to existing ones, build a concept graph or knowledge map, surface forgotten related discussions ("you talked about this with investor X 3 months ago"), extract entities and relationships from unstructured text, or turn scattered thoughts into wiki-style atomic notes. Also trigger when the user mentions "second brain", "Zettelkasten", "PKM", "personal knowledge management", "note graph", "knowledge graph", "link my notes", "organize my vault", "connect ideas", or asks Claude to "remember" something across sessions using Obsidian. If the user is doing anything with Obsidian notes and wants intelligence layered on top, use this skill.
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。
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
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。
Manages scaling for GKE workloads using HPA and VPA. Use when configuring Horizontal Pod Autoscaler (HPA), configuring Vertical Pod Autoscaler (VPA), or applying best practices for GKE workload autoscaling. Do not use for cluster-level autoscaling (Cluster Autoscaler), static cluster sizing, or configuring node-level machine styles directly.
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。
Decision guide for delegating to caveman-style subagents. Tells the main thread WHEN to spawn `cavecrew-investigator` (locate code), `cavecrew-builder` (1-2 file edit), or `cavecrew-reviewer` (diff review) instead of doing the work inline or using vanilla `Explore`. Subagent output is caveman-compressed so the tool-result injected back into main context is ~60% smaller — main context lasts longer across long sessions. Trigger: "delegate to subagent", "use cavecrew", "spawn investigator/builder/reviewer", "save context", "compressed agent 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。
Use when the user wants to create, generate, build, update, refresh, or improve their personal writing style guide from their own sent writing (Generate mode), OR when they ask the agent to write, draft, reply, rewrite, edit, polish, or humanize something in their voice (Use mode). Teach your agent how to write like you.
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。
Improve code structure without changing behavior. Use when refactoring, restructuring, simplifying, or extracting code. Also for reducing duplication, renaming for clarity, or addressing code smells. Enforces one change → test → commit cycle. NOT for style/formatting (use /lint), features, or bug fixes.
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。
Restate content as a flat list of atomic facts in the style of av/facts fact sheets. Use when the user says "just facts", "facts only", "as facts", "give me the facts", or replies with a bare "facts" / "facts?" to a previous message — then the scope is that message's content.
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。
Firmware development for the LGT8F328P-LQFP32 MiniEVB — the Nano-style 30-pin "purple nano" board whose silkscreen reads LGTBF32BP (also sold as BTE21-15A, WAVGAT, LGT8F328P Nano V3.0), built on the Logic Green / Prodesign LGT8F328P, an AVR-instruction-compatible LGT8XM part with a 32 MHz internal RC and no crystal, a 12-bit ADC, an 8-bit DAC on D4, four timers, 80 mA drive pins, SWD instead of ICSP, and EEPROM emulated in program flash. Use when working on this board, any LGT8F328P/LGT8F328D/LGT8FX8P board, or a sketch being ported from an Arduino Nano or ATmega328P: PlatformIO setup with the lgt8fx core, platformio.ini, f_cpu/f_osc/clock_source and why timings come out 2x wrong, pin mapping and the LQFP32 bonded pads, analogRead resolution and reference errors, analogWrite hitting the DAC, EEPROM vanishing after upload, 80 mA outputs, upload failures over CH340/CH9340/HT42B534, SWD recovery, or debugging why something on the board does not 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。
Master of low-and-slow BBQ, smoking techniques, rubs, and regional American BBQ styles
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。
Game art principles. Visual style selection, asset pipeline, animation workflow.
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。
Add, edit, or audit guidance docs. Default writes guidance for Claude (.claude/guidance/, Markdown, moflo universal rules). -h writes for human readers (docs/, lighter ruleset). --html emits HTML with a minimal default stylesheet instead of Markdown. -a audits the .claude/guidance/ directory.
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。
Step-by-step release checklist for Squad — prevents v0.8.22-style disasters
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。
Microsoft Style Guide + Squad-specific documentation patterns
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 creating scientific magazine cover style images or prompts, research hero visuals, journal-cover-inspired concepts, academic poster covers, PPT covers, and high-impact scientific visual concepts. If the user asks to generate the image, use ChatGPT image generation.
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。