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概要と使いどころ
Creates structured plans from requirements. Generates comprehensive plans with steps, dependencies, risks, and success criteria. Coordinates with specialist agents for planning input and validates plan completeness. Uses template-renderer for formatted output.
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PowerPoint presentation generation using python-pptx. Create slides from Claude output, data analysis, or structured content. Covers slide templates, shapes, charts, tables, and themed presentations. Use for generating .pptx files programmatically.
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 Product Requirements Documents using hypothesis-driven methodology with Implementation Phases tracking.
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。
Sequential thinking and structured problem solving. Break down complex problems into steps with revision and branching capabilities. Use for multi-step analysis, planning, and hypothesis verification.
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-first security scanning with Medusa. 3,000+ detection patterns covering AI/ML, agents, MCP, RAG, prompt injection, and traditional SAST vulnerabilities. Wraps Medusa CLI with SARIF/JSON parsing, structured finding output, OWASP mapping, and remediation guidance.
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。
Structured interactive questionnaire framework for gathering requirements from users. Uses A/B/C/D/E multiple choice patterns with additive vs exclusive question classification.
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。
Structured workflow for upgrading Next.js applications across major versions. Use when migrating a Next.js project from one major version to another (e.g., 13 to 14, 14 to 15, 15 to 16). Covers codemod automation, breaking change detection, incremental migration paths, and post-upgrade validation.
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。
Transforms vague UI/feature requests into structured, optimized prompts with design system awareness. Use when generating prompts for UI implementation, feature specification, or design-to-code translation. Triggers on tasks requiring prompt refinement, UI specification, or design system integration.
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 structured incident response runbooks with step-by-step procedures, escalation paths, and recovery actions. Use when building runbooks, responding to incidents, or establishing incident response procedures.
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。
Verify fix commits address security findings without introducing new bugs or regressions. Analyzes diffs for anti-patterns like removed validation, weakened access control, reduced error handling, reordered external calls, and changed integer operations. Generates structured FIX_REVIEW_REPORT with finding status tracking.
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 development with structured merge/PR options. Use when ready to merge or submit 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。
Workflow for repository reconnaissance and operations using GitHub CLI (gh). Optimizes token usage by using structured API queries instead of blind file fetching.
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。
Structured debug log analysis for Claude Code sessions — auto-discovers most recent log, runs reducer, extracts error patterns, correlates with full log, produces observability report. Fills 5 identified gaps: hook error body capture, agent identity, file path tracking, stall correlation, success visibility.
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。
Multi-step autonomous research methodology for deep investigation tasks with structured synthesis
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。
Collaborative document creation via a structured three-stage workflow. Use for writing specs, PRDs, design docs, proposals, RFCs, and any long-form document where quality and clarity matter. Brainstorms 5-20 options per section, builds iteratively, and tests with reader sub-agents.
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。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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。
Commission a project to an SDLC option bundle (solo / single-team / programme / assured). Asks structured questions, recommends an option × level, installs the bundle, and records the decision in .sdlc/team-config.json.
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。
Query the project knowledge base. Wraps the research-librarian agent. The librarian reads the shelf-index, identifies the 2-4 most relevant library files for the question, deep-reads only those, and returns structured evidence with citations. Stateless — reads the index fresh on every query.
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。
Health-check the project knowledge base. Looks for contradictions between files, stale claims that newer sources have superseded, orphan files with no inbound cross-references, important concepts mentioned but lacking their own page, missing cross-references, and data gaps. Returns a structured report; does not auto-fix.
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。
Dispatch a structured cross-phase review of a phase artefact. MANDATORY for design-spec and test-spec; the gate validator checks for the resulting review record before passing. Recommended for requirements-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。
This skill should be used when the user wants to build, set up, or operate an AI "second brain" — a persistent memory vault (Obsidian-compatible Markdown) that lets an AI agent resume work without re-explaining context, remembers correction instructions across sessions, and auto-organizes raw material into structured knowledge. Trigger on requests like "build my second brain", "set up an Obsidian vault for AI", "give my AI persistent memory", or "make AI stop forgetting".
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。
Prevents premature execution on ambiguous requests. Analyzes request clarity using 5W1H decomposition, surfaces hidden assumptions, and generates structured clarifying questions before work begins. Use at the start of any non-trivial task, or when a request could be interpreted multiple ways. Triggers on "뭘 원하는건지", "요구사항 정리", "clarify", "what exactly", "scope", "requirements", "정확히 뭘", "before we start".
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。
Devil's Advocate stress-testing for code, architecture, PRs, and decisions. Surfaces hidden flaws through structured adversarial analysis with metacognitive depth. Use for high-stakes review, stress-testing choices, or when the user wants problems found deliberately. NOT for routine code review. Triggers on "스트레스 테스트", "stress test", "devil's advocate", "반론", "이거 괜찮아", "문제 없을까", "깊은 리뷰", "critical review", "adversarial".
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。
Search the web with Exa AI — neural search, content extraction, similar page discovery, quick research with citations, and async pro research with structured output. Covers all Exa endpoints (/search, /contents, /findSimilar, /answer, /research/v0/tasks). Triggers on web search, find pages, similar pages, research with citations, Exa, neural 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。