4,425 件 ・ 関連度順
概要と使いどころ
Draft a Workflow Phase 1 intake document capturing a new request — the problem, the desired outcome, constraints, and testable acceptance criteria. Use when a user brings a new feature, change, or investigation that doesn't yet have a spec. The output lives at `docs/intake/<slug>.md` and feeds `/scout`, `/research`, and `/spec` downstream.
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。
Orchestrates `impeccable` for every design task inside a workflow phase. Captures intent in natural language, classifies it (design / development / copy), translates design intents into a sequence of impeccable subcommand invocations, runs them in main context with state persistence at `.claude/state/design/<slug>.json`, and returns a structured report. ALWAYS invokes `impeccable` under the hood for the underlying design move; never picks aesthetic direction itself; never writes product code directly. Per CLAUDE.md Article X.2, all design tasks in workflow phases route through 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。
PM-mode brainstorm helper. Captures the requirement via Socratic dialogue before any entry phase (`/intake`, `/spec`, `/tdd`) drafts its artifact. Stage 0 skip-check, Stage 1 gap-analysis, Stage 2 probe-loop, Stage 3 confirm-and-persist. Output lives at `docs/brief/<slug>.md`. Never proposes solutions — Stage 2 dialogue discipline is structurally enforced via `discipline.mjs`.
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 for prioritization, or when there are more tasks than capacity: "what should we do first?", "rank this backlog", "cut scope for the MVP", "RICE score these". Picks a method (RICE, ICE, MoSCoW, impact-effort), scores items and sets a cut line. Skip for choosing between two designs.
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 for Fermi estimation, or when a rough number is needed fast: "roughly how many...", "ballpark the cost", "estimate capacity or market size", "is this even feasible?". Decomposes, uses ranges and sanity-checks. Skip when exact data is available or a precise calculation is wanted.
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。
Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.
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。
Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks.
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 image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.
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 agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
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 patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical 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。
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
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。
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks
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。
Diagnose why an existing implementation differs from reference evidence using AE/SSIM, pixel, section, computed-style, and transition diffs. Use for post-implementation mismatch or repair guidance; not baseline capture or full clone 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。
Clone or recreate a live website URL, page, or section as React + Tailwind with extracted DOM, CSS, assets, responsive layout, motion, and interactions. Use for live-URL implementation or fidelity repair; not capture-only or diff-only 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。
Multi-layer validation to catch bugs before they escape
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。
当用户需要做重大决策、团队存在群体思维、或想将决策权下放到一线时触发此技能。帮助建立知情指挥决策模型，让最有信息的人做最终决定。
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。
Guide for creating effective skills following best practices. Use when creating or updating skills that extend agent capabilities.
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。
学术论文图表生成与设计。输入是实验数据（CSV/表格）、图表草稿、论文方法描述、中文图/表说明、想生成的图形摘要（GA）、或想画流程图时使用。功能包括：matplotlib 绘图（plot）、图表类型推荐（recommend）、英文图/表标题生成（caption）、论文架构图 prompt 生成（architecture）、图形摘要 prompt 生成（abstract）、流程图 prompt 生成（flowchart）、图表规范检查（polish）、概念图/示意图设计（design）。架构图模板覆盖 6 类场景，流程图覆盖 6 类（线性 / 分支 / 并行 / 循环 / 嵌套 / 泳道），图形摘要覆盖 5 类。内置 prompt 工程词汇表与参数化语法。不适用于：正文段落润色（用 academic-writing）、参考文献格式（用 academic-citation）。
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。
Recall project knowledge, past decisions, failures, and preferences when they can help a coding task. Capture changed files before responding.
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。
Learns a user's personal writing and speaking style through interactive writing prompts, then generates a reusable voice profile. Use when the user says "learn my writing style," "write like me," "capture my voice," "voice calibration," "mimic my tone," "my writing style," or wants AI to match their personal communication style. Also activates when a .voice-profile.md file exists and the user asks you to write something in their voice.
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。
Mark a rolling-wave slice done on explicit user authority, regardless of its current lifecycle status or missing implementation, finalization, review, verification, or child-project state. Use when the user says a slice is done, complete, finished, accepted, or should be marked done; capture available material learnings, update project state, and output roadmap progress without requiring earlier workflow steps.
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。
Summarizes uncommitted git changes in a concise machine-readable format. Use in CI pipelines, scripts, or headless invocations where the output will be piped or captured.
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。
Subagent flow for deep-reading GitHub issues + their linked/closing PRs to the bottom. Captures CURRENT state, maintainer status updates, reporter repro, blocking reviewer concerns, hidden second bugs, cross-repo duplicates. Invoked by weekly-report orchestrator; runs as a general-purpose subagent so the orchestrator's context stays small.
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。
Deep enrichment for community-sourced enterprise PROSPECTS (the 🎯 Prospective enterprise customers subsection). For each prospect, resolve their LinkedIn from their GitHub self-linked accounts FIRST (search only if none is self-linked), verify the employer matches, capture their full name, then list the company website + company size (ARR / latest funding round / employee count). Runs as a general-purpose subagent (many web searches) so the orchestrator's context stays small. Invoked by weekly-report (enterprise section) and the enterprise 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。