「wants」の検索結果

Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE data.

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。

Evaluate ENCODE experiment quality using standard metrics and audit flags. Use when the user asks about data quality, wants to filter for high-quality experiments, needs to interpret quality metrics (FRiP, NSC, RSC, NRF, IDR, TSS enrichment, fragment size), wants to understand ENCODE audit warnings, needs to compare quality across experiments, or is deciding whether data is usable for their analysis. Also use when the user mentions QC, quality control, or data filtering.

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。

Rapid UI prototyping — generates 3 visually distinct HTML/CSS components from a text prompt and serves them in a live browser gallery. Use when user runs /prototype, asks to "prototype a UI", "mock up a component", "generate HTML mockups", "create UI variations", "design exploration", "quick UI concept", or wants to see multiple visual approaches to a component. Also trigger when user says "show me different ways to build...", "explore different designs for...", or wants rapid visual exploration of a UI idea — even without saying "prototype" explicitly.

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

Teach a topic, video, article, codebase change, spec, or transcript until the user demonstrably understands it, using staged instruction, a running checklist doc, and quizzes. Use whenever the user says "teach me", "explain this in detail", "help me understand X", "/teach-me", "walk me through this", "I want to learn X", "understand this deeply", or pastes a YouTube URL, article, paper, PR, or spec and asks to understand it rather than summarize it. Also use when the user wants study notes or raw material from a source they are learning. Do NOT use for a quick factual lookup, a summary request, or when the user just wants the 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。

JLCPCB PCB fabrication and assembly — BOM/CPL generation, basic vs extended parts, assembly constraints, design rules, ordering workflow. Use with KiCad for JLCPCB manufacturing. Use this skill when the user mentions JLCPCB, wants to order PCBs or assembled boards, needs prototype bare PCBs and stencils, wants to know JLCPCB design rules and capabilities, or is asking about PCB manufacturing costs or turnaround times. For gerber/CPL export, stencil ordering, and BOM management, see the `bom` 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。

Build a structured interview scorecard for a role. Use when the user says "create an interview scorecard", "build an interview guide", "what questions should I ask for this role", "help me evaluate candidates consistently", "design the interview process", or wants to assess candidates against defined criteria - even if they don't explicitly say "scorecard". Also use when a recruiter or hiring manager wants to prevent gut-feel hiring.

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 UX tasks from a product spec and save as ux-tasks.md in the same spec folder. Use this skill when: - The user wants to generate UX work items from a spec - The user says "UX tasks", "what does UX need to do", "extract UX work", "UX deliverables" - The user wants to hand off a spec to the UX/design team - The user asks "what screens need designing" or "what UX decisions are open"

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。

Rate any product, feature, or experience on the 11-star scale (Brian Chesky's Airbnb thought experiment). Use when user says "rate this experience", "11-star", "star rating", "experience audit", "how good is this", "experience rating", "product audit", "quality assessment", or wants to evaluate product quality and identify improvement paths. Also trigger when user wants to benchmark a feature, assess where a product stands, or map out what "great" looks like - even if they don't explicitly say "11-star".

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。

Structure and run a post-interview candidate debrief. Use when the user says "run the debrief", "how do we decide on this candidate", "let's calibrate", "we need to make a hire/no-hire call", "prep the debrief meeting", or wants to structure the decision-making process after interviews are complete - even if they don't explicitly say "debrief". Also use when a recruiter wants to prevent groupthink or HiPPO effect (highest paid person's opinion) from dominating the decision.

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 transcripts from YouTube videos. Use when user says "get transcript", "fetch transcript", "YouTube transcript", "pull captions", "what does this video say", or pastes a YouTube URL and wants the text content extracted. Also use when user wants to research or summarize a YouTube video.

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。

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。

Close the loop on a Caveman learn report — review the ranked token sinks and apply cost-lowering fixes (trim config, offload recurring context to cavemem) with per-edit consent. Use when the user runs "caveman learn", asks to lower their agent's token cost, wants to trim a heavy CLAUDE.md, or wants to offload context they re-paste every session into cavemem.

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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 or update a strategic project roadmap with major milestones. Generates .unikit/ROADMAP.md — a high-level checklist of project goals. Use when user says "roadmap", "project plan", "milestones", "what to build next", "strategic goals", or wants to see big-picture progress. Also use when the user asks to check which milestones are done or wants to plan the overall project direction.

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。

Ideate a brand-new game concept with the user, from a blank page or a one-line hint to a finished CONCEPT card. Use it whenever the user wants to come up with a new game — whether the project has no design document yet, or already has one and they're exploring a fresh idea. Through a structured divergence/convergence dialogue it explores ideas, frames the hook, generates and scores concepts (market validation delegated to /unikit-gd-explore), and settles pillars, loops, motivation, and a pre-mortem. Trigger whenever the user wants to make or invent a game, doesn't know where to start, or gives a genre/theme hint, e.g. "let's come up with a game", "I don't know what game to make", "I want to make a roguelike", "a game about zombies", "a farming game", "help me come up with a concept". For researching or dissecting existing games use /unikit-gd-explore; to write an already-chosen concept as the master GDD use /unikit-gd-spec.

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 a short, project-specific rule, convention, or override to .unikit/RULES.md — the quick-capture inbox for this project's rules (common rules always load; topic files in .unikit/rules/ load when the work matches), automatically loaded by /unikit-implement (later promotable via /unikit-memory migrate-rules). Works only with a rule typed as a prompt — it does NOT read files, folders, URLs, or PDFs. Cross-checks against the knowledge base (RULES_INDEX.md) to avoid duplicating core/stack entries. Use for fast, one-line conventions and corrections: "add a rule", "remember this", "convention", "always do X", "never use Y", "from now on do Z", or when the user corrects agent behavior and wants it remembered; also "split the rules into topics" (optimise), "clean up the rules" (prune), "shorten RULES.md" (compact). If the user points to a source (file, folder, URL, PDF, article, book) or wants to research/document framework usage, use /unikit-memory; for architecture decisions use ARCHITECTURE.md.

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。

Cold-start brownfield reconnaissance — reconstruct the WHOLE game design from an existing codebase when there is no GDD yet. Optionally accepts a free-text game description, notes, or reference links to guide and enrich the scan. Use when the user wants to build the game design from the code, e.g. "create a GDD from this codebase", "reconstruct the design from our code — it's a roguelike deck-builder", "build a design doc from the existing project, here are some refs". Scans the project (engine auto-detected), extracts a system roster + dependency graph and content-type schemas / resources / entities into one passive .unikit/gamedesign/RECON.md, tags every fact provenance:extracted-from-code, and writes a mandatory Intent Gap for what code cannot know (pillars, fantasy, the "why"). Writes nothing else and calls no skill. STRICTLY whole-project cold-start — if a GDD already exists and the user wants a specific part investigated, use /unikit-gd-explore (code lens); to author the GDD use /unikit-gd-spec.

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。

When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' 'who is my target audience,' 'describe my product,' 'ICP,' 'ideal customer profile,' or wants to avoid repeating foundational information across marketing tasks. Use this at the start of any new project before using other marketing skills — it creates `.agents/product-marketing.md` that all other skills reference for product, audience, and positioning context.

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。

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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-driven development with a red-green-clean loop, running mix credo on the whole project at the end of every vertical slice so standards violations are fixed in the slice that introduced them instead of piling into a refactor at the end. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.

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 10 advanced AI agent node types for any DSL/runtime system — plan compiler, code interpreter, critique loops, intelligent routing, multi-agent ensemble, persistent memory, external API tools, iterative loops, data transforms, and parallel execution. Use this skill whenever the user wants to add agent capabilities to a workflow engine, build an AI orchestration framework, implement Karpathy-style AI upgrades, add new node types to a DSL runtime, or create autonomous agent pipelines. Also trigger when the user mentions AetherLang, flow engines, node types, agent frameworks, or wants to upgrade their AI system with capabilities like self-programming, reflection, routing, ensemble, memory, or tool use.

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。