「agent-skills」の検索結果

Runs a sequenced monolith-to-modular pipeline that sizes and inventories components, finds shared domain duplication, addresses flattening and hierarchy issues, analyzes coupling, then groups components into candidate domain-aligned units, with optional embedded DDD strategic analysis for bounded contexts. Use when asking how to split a monolith, size components before extraction, find duplicated domain logic, clean up module hierarchy, measure coupling between modules, or group components into services. Do NOT use for phased extraction roadmaps or prioritization without the prior analysis steps (use decomposition-planning-roadmap after this pipeline), end-to-end legacy migration strategy writeups (use legacy-migration-planner), pure infrastructure capacity sizing, or when you only need DDD without the structural pipeline (install domain-analysis standalone).

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 planning legacy system migrations, codebase modernization, monolith decomposition, microservices consolidation, cross-language rewrites, or framework upgrades. Invoke for strangler fig pattern, incremental migration strategy, or refactoring roadmaps. Do NOT use for domain analysis (use domain-analysis), component sizing (use component-identification-sizing), or step-by-step decomposition plans (use decomposition-planning-roadmap).

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。

Scores how completely an implementation fulfills a PRD/spec, case by case, and produces a single comparable final grade. Invoke only when explicitly named (e.g. run spec-driven-eval); do not auto-trigger. Use when benchmarking spec-driven implementations, grading acceptance criteria, evaluating whether a feature was 100% implemented, comparing multiple implementations of the same PRD, or auditing implementation and test coverage (unit and e2e) against product requirements. Do NOT use for planning or building features (use tlc-spec-driven), writing PRDs, or general code review unrelated to a 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。

Guide for creating AI subagents with isolated context for complex multi-step workflows. Use when users want to create a subagent, specialized agent, verifier, debugger, or orchestrator that requires isolated context and deep specialization. Works with any agent that supports subagent delegation. Triggers on "create subagent", "new agent", "specialized assistant", "create verifier". Do NOT use for Cursor-specific subagents (use cursor-subagent-creator 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。

Expert guide for designing and building high-quality skills from scratch through structured conversation. Use when someone wants to create a new skill, build a skill, design a skill, or asks for help making Agents do something consistently. Also use when someone says "turn this into a skill", "I want to automate this workflow", "how do I teach my Agent to do X", or mentions creating SKILL.md files. Covers standalone skills and MCP-enhanced workflows. Do NOT use for creating subagents (use subagent-creator) or technical design documents (use create-technical-design-doc).

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。

Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment". Do NOT use for deploying to Netlify, Cloudflare, or Render (use their respective 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。

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare. Do NOT use for deploying to Vercel, Netlify, or Render (use their respective 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。

Use when a question, decision, plan, tradeoff, or claim needs a rigorous verdict and one perspective is not enough. Spawns a panel of 3 to 5 subagent jurors that form independent blind opinions, deliberate anonymously under an anti-anchoring and anti-sycophancy protocol, and return one committed verdict with confidence, preserved dissent, and a concrete next action. Domain-agnostic across engineering, architecture, data, product, hiring, strategy, vendor choice, build-vs-buy, and research design. Trigger phrases include "convene a jury", "have agents debate and decide", "get a panel to decide", "multi-agent decision", "stress-test this and decide", "monte um juri", "tribunal de agentes", "painel para decidir". Do NOT use to only critique without deciding (use the-fool for that), to build a plan or write the solution itself, or for simple factual lookups.

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。

Interviews an unshaped idea into a verdict and a design document - decisions, flows, schema, contracts - that anyone can plan from without having been in the room. Use when the user says "research this", "help me understand this problem", "should we build this", "discovery", "explore this problem", or "tlc-discover". Do NOT use to cut a finished design into tasks, or to implement.

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。

Creates structured Request for Comments (RFC) documents for proposing and deciding on significant changes. Use when the user says "write an RFC", "create a proposal", "I need to propose a change", "draft an RFC", "document a decision", or needs stakeholder alignment before making a major technical or process decision. Do NOT use for TDDs/implementation docs (use technical-design-doc-creator instead), README files, or general documentation.

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 build an AI-powered outreach system, write cold emails, improve deliverability, or scale personalized outreach. Also use when the user mentions 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' or 'outreach stack.' This skill covers the complete AI cold outreach system from signal detection through conversion. Do NOT use for technical implementation, code review, or software architecture.

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。

Creates Cursor-specific AI subagents with isolated context for complex multi-step workflows. Use when creating subagents for Cursor editor specifically, following Cursor's patterns and directories (.cursor/agents/). Triggers on "cursor subagent", "cursor agent". Do NOT use for generic subagent creation outside Cursor (use subagent-creator 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。

Technology-agnostic guidance for modular systems: bounded contexts, clear boundaries, composability, state isolation, explicit contracts, failure containment, scaffolding workflows, split/merge criteria, sub-units inside a context, and compliance review signals. Use when designing or reviewing module structure, service boundaries, package layout, cross-cutting dependencies, "how should we split this?", modularity assessments, coupling between domains, greenfield context design, or architecture discussions without assuming a specific framework, language, or repository layout. Do NOT use for executing the full Patterns 1–5 repo decomposition pipeline or per-pattern inventories (use modular-decomposition), phased extraction roadmaps as the main deliverable (use decomposition-planning-roadmap), or end-to-end legacy migration strategy (use legacy-migration-planner).

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。

Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices". Focuses on visual design and interaction patterns. Do NOT use for performance audits (use core-web-vitals), SEO (use seo), or comprehensive site audits (use web-quality-audit).

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 a work already planned: extracts a checklist, builds it, and proves every check with an independent verifier. Use when the user says "extract a checklist", "build this ticket", "implement this spec", or "tlc-implement". Do NOT use when nobody has decided what to build, or to design the 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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications. Generates creative, polished code that avoids generic AI aesthetics. Do NOT use for design review or audit (use web-design-guidelines or web-quality-audit).

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。

Feature planning and implementation with 4 adaptive phases (Specify, Design, Tasks, Execute). Auto-sizes depth by complexity. Writes testable requirements in EARS notation, atomic tasks, atomic Conventional Commits, and requirement traceability. Ships deterministic Python validation scripts so structural gates are enforced by code, not memory. Features an independent Verifier (author != verifier, evidence-or-zero), a discrimination sensor, a decision log (STATE.md), a test-coverage matrix, and a self-improving lessons layer. Stack-agnostic and tool-agnostic. Use when (1) planning features, (2) implementing with verification and atomic commits, (3) validating an implementation against a spec. Triggers on "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "record decision", "pause work", "resume work". Do NOT use for pure architecture decomposition analysis or standalone technical design documents.

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 decided work — a PRD, design doc, RFC, or thread — into tasks a builder can act on without guessing. Finds slices that each prove something, grounds them in the code, and writes intent, observable criteria with concrete values, the boundary, what the change disturbs, and only the decisions that are hard to reverse. Walks every surface the work exposes and sweeps the nine unwritten requirements, recording each landing as a criterion already in the source, existing behaviour, n/a, or Unresolved — never as a criterion the walk invented. Defaults to one task per source. Use when the user says "write the task", "cut this PRD into tasks", "turn this design doc into work", or "tlc-plan". Do NOT use for discovery itself or to implement — a one-line ticket is a decision; a blank wish is not.

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。

Creates comprehensive Technical Design Documents (TDD) with mandatory and optional sections through interactive discovery. Use when user asks to "write a design doc", "create a TDD", "technical spec", "architecture document", "RFC", "design proposal", or needs to document a technical decision before implementation. Do NOT use for README files, API docs, or general documentation (use docs-writer 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。

Complete Shopify development reference covering Liquid templating, OS 2.0 themes, GraphQL APIs, Hydrogen, Functions, and performance optimization (API v2026-01). Use when working with .liquid files, building Shopify themes or apps, writing GraphQL queries for Shopify, debugging Liquid errors, creating app extensions, migrating from Scripts to Functions, or building headless storefronts. Triggers on "Shopify", "Liquid template", "Hydrogen", "Storefront API", "theme development", "Shopify Functions", "Polaris". Do NOT use for non-Shopify e-commerce platforms.

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。

Detects anemic domain models, validates and refactors them into rich domain models, and enforces tactical DDD patterns (Entities, Value Objects, Aggregates, Domain Services, Domain Events). Use when the user asks to validate, review, or check domain models or DDD code; detect anemia; refactor domain objects; improve encapsulation; or mentions terms like "anemic model", "rich domain", "aggregate", "value object", "domain event", "ubiquitous language", "is this good DDD", "does this follow DDD", or "check my domain". Do NOT use for module or service boundary design, architectural decomposition, strategic DDD context mapping, or code outside the domain layer (DTOs, controllers, infrastructure adapters).

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 the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Use when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting. Covers general Figma data fetching and exploration. Do NOT use when the goal is specifically pixel-perfect code implementation from a Figma design (use figma-implement-design 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。

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, modifying, or reviewing code — implementation tasks, code changes, refactoring, bug fixes, or feature development. Do NOT use for architecture design, documentation, or non-code 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。

Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Use when the user provides Figma URLs or node IDs and asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection. Do NOT use for general Figma data fetching, variable exploration, or MCP troubleshooting (use figma 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。