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概要と使いどころ
Use only when the user explicitly types `/orchestrate goal` to decompose a large task, spawn a tree of parallel cloud-agent workers/subplanners/verifiers via the Cursor SDK, and collect structured handoffs; do not invoke autonomously.
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。
Designs or reviews CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the user mentions agents, terminals, or automation-friendly CLIs.
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。
Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.
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。
Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.
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。
Provides Rust coding best practices for structure, patterns, performance, and error handling. Use when writing or reviewing Rust code, or when the user asks for Rust style 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。
Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, or build a new 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。
Refactor code to improve quality while maintaining functionality. Use when you need to improve code structure, eliminate duplication, optimize performance, or enhance maintainability without changing behavior.
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 Mermaid diagrams from code, architecture, or concepts. Use when you need to visualize code flow, system architecture, data relationships, state machines, sequences, class structures, or any other diagrammable concept.
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。
Refactor and review SwiftUI view files for consistent structure, dependency injection, and Observation usage. Use when asked to clean up a SwiftUI view’s layout/ordering, handle view models safely (non-optional when possible), or standardize how dependencies and @Observable state are initialized and passed.
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。
Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing.
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。
UI spec 與 Panel scaffold SKILL — 以 normalized recipe、family defaults、content contract 產出或更新 screen package 與 CompositePanel / ChildPanel TypeScript 骨架。USE FOR: 新 screen 從 recipe 落地、既有 screen 做 structure normalization、需要執行 compile-recipe-to-screen-spec.js / compile-recipe-to-panel-scaffold.js。DO NOT USE FOR: 最終視覺 QA、手工 Prefab 微調當正式流程。
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 fast, read-only health check across all skills in the library and produce a structured quality report — without modifying anything. Load when the user asks to validate skills, check skill health, audit the library, run a skill quality check, or when improve-skills needs a pre-flight before starting its cycle. Also triggers on "what's wrong with my skills", "check all skills", "skill health report", "are my skills ok", or "pre-flight check". Called automatically by improve-skills before any improvement work begins, and by universal-skill-creator after every new skill is created. Never modifies any file — only reads and reports.
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。
Automatically maintain skill library consistency whenever a structural change occurs — new skill added, skill renamed, skill deprecated, call graph rewired, or category changed. Updates SKILL-INDEX.md, AGENTS.md, README.md, skill graph, docs/prd/PRD.md, and docs/architecture.md. Load when universal-skill-creator finishes creating a skill, split-skill extracts a child, deprecate-skill retires a skill, improve-skills makes a structural change, or the user manually renames or restructures skills. Also triggers on "update the skill index", "sync skill references", "refresh the skill graph", "fix broken skill cross-references", or "update docs after skill 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。
Orchestrator for agent harness work — the setup that makes AI agents follow project rules and improve when they fail. FIRES PROACTIVELY when agents misbehave, repeat mistakes, ignore instructions, skip skills, or when AGENTS.md exists but docs/harness/manifest.json is missing. Also triggers on: harness engineering, agent scaffold, agent keeps failing, agent not following instructions, make agents reliable, agents going off rails, agent forgot context, improve agent setup, self-improving agents, agents keep making mistakes, why is my agent bad, agent quality, agent setup broken, agents ignore skills, same mistake again, fix agent behavior, tune agent instructions, set up agent infrastructure, after project setup agents still bad. Routes bootstrap vs evolution. Not multi-agent topology — agent-builder.
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 5–10 business idea candidates from a blank page or a founder's domain context — using pain mining, jobs-to-be-done, trend × capability mapping, constraint relaxation, adjacency search, and founder-market-fit prompts. Each candidate is a structured idea card (segment, JTBD, current alternative, why-now, distribution wedge, monetisation, "feels like"). Load when the user asks to generate business ideas, brainstorm startup ideas, find ideas to work on, says "what business should I start", "give me startup ideas", "I don't know what to build", "ideate ventures", "blank-page idea generation", "find me a startup idea", "explore business opportunities". Sub-skill of `venture-exploration`. Hard-bans "Uber for X" / "AI for X" with no specific JTBD, "everyone" segments, and idea cards missing any of the 7 required fields. Does NOT design or evaluate ideas generated — for that use `idea-evaluation`.
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, improve, and compress every skill in the repo using live research. Load when the user asks to improve skills, audit the skill library, upgrade existing skills, refresh with new research, do a skill health check, or says "improve all skills", "update the skill library", "skill audit", or "run an improvement pass". Applies live domain research, fixes structural gaps, checks for skill linking opportunities, then rewrites and resizes each skill. Supports TARGETED mode (`TARGET=<skill> [SKIP_RESEARCH=true]`) for single-skill fixes, including learn-from-chat restructure escalations. All skills are in scope including meta skills.
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, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".
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 user-facing or internal release notes and changelogs. Load when the user prepares a release, tags a version, or wants to summarize recent progress. Also triggers on "write a changelog", "prepare release notes", "what's new in this version", "summarize my commits", or "create a release summary". Auto-triggered by library-skill after major repo changes (new skills added, skills renamed, structure changes). Applicable to any project, including this skill library itself.
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。
Orchestrator for the eval-output skill suite — evaluate LLM and agent outputs for quality, accuracy, helpfulness, and safety using structured rubrics and LLM-as-judge techniques. Load when the user says "evaluate this output", "score this response", "run an eval", "LLM as judge", "evaluate agent output", "how good is this response", "rate this answer", "eval this", or provides an LLM output that should be assessed for quality. Single entry point for all output evaluation workflows.
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。
Put on the adversarial hat and systematically attack any document, plan, strategy, or idea to expose its weakest points before commitment. Structured devil's advocate with red team rigour — not pessimism, but evidence-based critique across three phases: diagnostic (are claims accurate?), creative (is the problem artificially constrained?), challenge (are solutions robust?). Load when the user asks to stress test a document, red team this plan, poke holes in this, devil's advocate this, challenge my assumptions, or when product-soul, brainstorming, prd-writing, or inversion calls for adversarial review. Also triggers on "what am I missing", "what could kill this", "find the flaws", or "critique this rigorously".
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 git work with atomic commits, conventional messages, short-lived branches, and pre-commit hygiene. Load when committing, branching, resolving merge conflicts, organizing parallel work, or reviewing git history. Also triggers on "git workflow", "commit message", "conventional commits", "atomic commit", "branch strategy", "git worktree", "how should I commit this". Does not replace project-specific hook policies — complements them.
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。
Quickly understand an unfamiliar codebase or project by mapping its architecture, identifying key components and data flows, and surfacing complexity hotspots. Load when the user asks to understand a repo, explain how something works, map the architecture, onboard to a codebase, or explore how components connect. Also triggers on "walk me through this codebase", "how does this project work", "explain the architecture", "what does this repo do", "show me the structure", "onboard me", or any request to build a mental model of a codebase before making changes.
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。
Design state-of-the-art multi-agent systems, orchestration patterns, and wiring from scratch. Load when the user asks to build an agent system from scratch, design agent orchestration patterns, choose between sequential/parallel/hierarchical workflows, or define how multiple agents should collaborate. Also triggers on "agent architecture", "multi-agent wiring", "agent orchestration pattern", "how to connect these agents", "design the communication structure". Called by agent-builder for complex topologies (>4 agents or hierarchical). For process-driven agent design, use agent-builder 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。
Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).
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。