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概要と使いどころ
Record a narrated video of a feature running in the local dev app, for a PR or a stakeholder. Drives a headless Chrome over the DevTools Protocol so clicks and keystrokes are real, captures frames, and encodes an mp4 with no extra tooling installed. Use when the user asks to "record a video", "make a demo", "show this working", or wants a screen recording of a change.
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 implementation and tests are complete and a human must choose how local branch work should be integrated or preserved
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。
One-shot GEO visibility check for a brand using Xpoz. Runs the buyer questions that matter through Claude, ChatGPT, and Gemini, and reports where the brand appears, who wins instead, and which surfaces the answers are assembled from. Use when asked to "check my AI visibility", "does ChatGPT recommend us", "GEO audit", "where do we show up in AI answers", or "who wins our category in AI 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。
Show where this machine's Claude Code tokens went - cost by token type, context tax per tool, biggest tool outputs.
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。
Estimate the full development cost of an existing codebase from lines of code, architectural complexity, and team-composition overhead. Use for 'how much would this cost to build', 'what did this codebase cost', development-cost or build-cost estimates, calendar-time estimates, and Claude/AI ROI on a delivered codebase. Estimates by measured LOC and complexity, not by ticket volume.
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。
Resolve CodeRabbit review feedback on a GitHub pull request. Collects every open CodeRabbit finding (inline threads, plus the nitpick and outside-diff findings packed into review bodies), judges and fixes each one against the real code with subagents, unifies fixes that share a pattern, commits locally, asks before pushing, then shows every reply draft linked to its finding and posts only on approval. Runs only on top-tier models. Use on "resolve the CodeRabbit feedback", "address coderabbit comments", "answer the rabbit", "fix what CodeRabbit flagged on
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。
Quick-reference card for all caveman modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /caveman-help, "caveman help", "what caveman commands", "how do I use caveman".
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。
Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.
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。
Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
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。
Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.
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。
Plan a content strategy, topic clusters, editorial roadmap, and content mix for traffic, authority, and lead generation. Use when deciding what to publish, what topics to prioritize, or how to structure a content program.
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。
Product Discovery through an 18-task methodology in 6 blocks — from market analysis to an investor-ready financial plan. Use when someone wants to run Product Discovery, validate a startup, assess a market hypothesis, prepare for an investment round, or raises an adjacent topic — idea validation, niche sizing, competitor teardown, product-market fit, pitch preparation, startup unit economics, geographic expansion into a new country, go-to-market for SEA / Asia / MENA. People rarely name PD explicitly; they say 'is there a market for this', 'assess my idea', 'I need a deck for an angel', 'we are entering Thailand/Singapore/UAE, how do we size it'. Use the skill in those cases too. Three modes: Light (~45 min, idea stage), Full (~2-3 h, MVP with customers), Geographic Expansion (~2 h, product entering a new geography). Produces 3-4 artifacts in /mnt/user-data/outputs/: one-pager.pptx, financial-plan.xlsx, presentation.pptx, optionally interview-guide.docx.
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 goal loop — give it ONE goal plus how to verify it, the agent runs check→fix→check itself and comes back only with the finished result (code with audit, research with fact-check, content with critique, audit/backtest). Self-verification instead of constant supervision, with hard safety guards. Vary the loop with a verification rubric designed before it runs. Triggers — "work autonomously to the result", "don't come back until it's done", "run the loop yourself", "drive it to done".
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。
One-sentence description of what this skill does. Shown as a tooltip on the chip.
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。
How to manually regenerate the compiled agentic workflow .lock.yml files when the gh-aw Version Check workflow reports version drift. All workflows track the newest github/gh-aw release or prerelease.
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。
Reports how local Git branches are progressing toward canonical upstream inclusion as a compact terminal table plus a browser-rendered HTML report, with branch purpose, stack dependencies, Git Machete topology, ahead/behind counts, change-request status, and next action. Use when asked for upstreaming status, local branch submission progress, which branches have change requests, or what remains before they can land.
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。
Turns an existing Product Requirements Prompt at .ai/[feature]/prp.md into a step-by-step task list of parent tasks and sub-tasks, saved to .ai/[feature]/tasks.md and committed. Use when a PRP is ready to be broken down into implementable work, or when planning how a feature will be built before any implementation starts. To write the PRP itself first, use prp- 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。
Root-causes one specific mistake the agent just made, such as not committing despite instructions to, by checking it against the loaded AGENTS.md, CLAUDE.md, skills, and Beads memories, delegating the investigation to a separate agent where the harness supports one; proposes concrete context improvements, and lets the user choose which to apply and how to remediate. Use when the user invokes `/learn` or `$learn`, with or without a description of the mistake, including `/learn /qs`-style shorthand naming the corrective command. For a broad end-of-session documentation sweep, use `documentation-updates` (`/reflect`) instead.
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。
Summarises the current session's status so a human can see where things stand and what happens next. Use when the user invokes `/sq`, asks for the status quo, session status, a catch-up, recap, or reminder where things got to, regardless of how much previous output there was.
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。
Produces an attorney-ready memo from a corpus of legal documents supplied by the user. Use when a user shows up with a folder, zip, or vault of case documents and asks for a case summary, case evaluation, litigation package, intake memo, matter overview, or "can you summarize this case for me." The skill ingests the corpus into a searchable index, OCRs anything non-searchable, inventories and diagnoses the practice area, loads the appropriate practice-area playbook module(s) (PI/tort, commercial litigation, IP infringement, or user-authored extensions), iteratively searches the corpus across eight core dimensions plus any module-specific dimensions, defers specialized document clusters (depositions, medical records, discovery, liens) to dedicated sibling skills, and synthesizes a cited memo.
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。
Citation format and verification protocol for legal documents that draw on Bates-stamped source records. Defines the bracket citation format, multi-source citation rules, quotation handling, the verification pass that runs before output, and the [UNVERIFIED] flag protocol. Use this skill any time another skill produces a legal work product that cites Bates-stamped pages, including medical chronologies, deposition summaries, demand letters, case briefs, and discovery responses. Also use any time the user asks how to format a citation or verify that a claim is supported by the source.
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。
Comprehensive reference for inter-process communication mechanisms -- every way processes can talk on a computer. Covers sockets (TCP, UDP, Unix domain), WebSockets, SSE, pipes (named/anonymous), shared memory (mmap, shm_open), message queues, signals, D-Bus, XPC (macOS), gRPC, REST, stdin/stdout, file-based coordination, and clipboard. Performance benchmarks, platform availability, and code examples for each. Special focus on which IPC works best for AI agent coordination. Activate on: "IPC", "inter-process communication", "process communication", "how do I talk between processes", "Unix socket vs TCP", "shared memory", "named pipe", "WebSocket vs SSE", "gRPC vs REST", "agent coordination IPC", "XPC service", "message passing", "stdout pipe", "D-Bus", "mmap". NOT for: distributed systems design (use distributed-systems), network protocol design (use networking), message queue infrastructure like Kafka (use data-pipeline-engineer).
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 vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).
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 stuck on a hard problem, decomposition is unclear, a related problem is needed, or explicit looking-back review will improve transfer. NOT for routine execution with a known procedure, rote checklist work, or domain questions that need specialized subject matter expertise instead of heuristic search.
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。