開発のスキル

Use when analyzing SonarQube issues and turning them into SPEC SDDs and tracked GitHub Issues for TDD implementation.

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 building a new MCP server in TypeScript, Python, or C# that exposes tools to LLMs.

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 reviewing code before it merges, whether written by an agent or a human.

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 the user asks to connect an AI agent to external apps via Composio, or when Composio CLI or MCP setup fails.

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 the migration of a legacy system or monolith — analyzes the source codebase (current repo, or a repo URL cloned to a temp dir) and produces an evidence-based Strangler Fig migration plan with per-domain SPECs. Default target is .NET (Blazor WebAssembly, .NET MAUI, ASP.NET Core); other stacks allowed by user decision. Do NOT use to implement code or when approved SPECs already cover the migration.

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 the user wants to configure, authenticate, or use Google NotebookLM via the nlm CLI or 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。

Use when generating or editing draw.io/diagrams.net architecture diagrams via MCP or native XML.

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 turning approved plans, specs, PRDs, or Epics into trackable GitHub Issues.

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 the user wants to improve architecture, consolidate tightly-coupled modules, or make a codebase more testable.

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 an evidence-backed working model of an existing codebase. Use when you must orient in a large or unfamiliar repository; explain architecture or a subsystem; trace a request, runtime, control, or data flow for a concrete question or bug; analyze a branch, commit, diff, or pull request for behavioral impact and blast radius; or assess AI-generated or changed code against requirements, contracts, invariants, tests, and runtime evidence. Default to read-only investigation. Do not trigger only because a coding task touches an existing repository; use when understanding or verification is the requested outcome or a substantial prerequisite.

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。

Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure

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 SwiftUI guidance for macOS apps — covers writing and reviewing code with runtime-level understanding of observation, concurrency, performance, and platform integration. Use when user asks to "build a SwiftUI view", "review my SwiftUI code", "fix observation issues", "bridge AppKit", "architect state management", "debug view updates", or works on any macOS SwiftUI project — building features, reviewing existing code, debugging view updates or performance, fixing concurrency issues, architecting state management, bridging AppKit, or making design decisions. Do NOT use for iOS/iPadOS-only SwiftUI, UIKit bridging, or basic Swift language questions. Focuses on non-obvious traps and deep patterns, not basics.

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Use when configuring or optimising GitHub repositories for cost-effective, consistent operations — CI triggers, Actions billing, issue tracking, labelling, branch protection, or release workflow.

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Validate agent output against declared domain rules and ground truth before trusting it downstream. Trigger after any agent produces output that will be used in a decision, stored persistently, or passed to another agent.

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。

Govern discovery, eligibility, and submission of a plugin or skill to official directories, registries, marketplaces, and curated GitHub lists. Use when preparing or sending plugin listings, marketplace forms, directory PRs, or repository recommendations; require current policy evidence and a final human confirmation before every external submission.

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Scaffold and govern an MCP server as a bounded tool seam. Defines which tools the agent may call, enforces the principle that agents call tools and tools call infrastructure. Trigger when adding or reviewing an MCP server in an agent system.

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Force plan, HLD, ADRs, and constraints to exist BEFORE any code is generated. Trigger when starting a new feature, epic, or significant change.

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Review gate for correctness, reuse, and simplification. Produces a structured verdict with actionable findings. Trigger on any PR before merge, or on any agent-generated code before it is committed.

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。

Ship an already-committed Git branch through GitHub: verify branch/worktree intent, push, create or mark a pull request ready for review, optionally wait for CI, optionally address review comments automatically, and merge with explicit safety gates. Use when a solo developer repeatedly asks to publish committed work, register a ready PR, handle PR feedback, and complete merge.

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。

Sync reusable frontend decisions into persistent project documentation after UI work. Use when frontend changes introduce or modify component APIs, variants, design-system tokens, styling conventions, layout behavior, accessibility rules, interaction patterns, responsive behavior, or agent operating instructions; when the user asks to reflect decisions in components.md, design system docs, AGENTS.md, CLAUDE.md, GEMINI.md, or similar project memory files; or before finalizing frontend work where future consistency depends on decisions made during implementation.

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。

Explore open-source GitHub repository source trees via web browsing to analyze and compare feature implementations at the code level. Supports two modes: cross-project comparison and single-project deep dive. Use when evaluating how OSS projects implement a specific feature, choosing architecture patterns, or benchmarking implementation strategies.

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。

Debug like Fable 5 — systematic root cause analysis with natural reasoning flow. Use this skill when you encounter an error, unexpected behavior, failing tests, or anything that does not work as intended.

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Think like Fable 5 — natural, flowing, purposeful reasoning distilled from 4,665 real chain-of-thought traces with mathematical precision. Use this skill EVERY TIME before writing code, making decisions, or taking action.

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。

Code like Fable 5 — methodical, verified, and deeply informed by context. Use this skill whenever you need to write, edit, or create code.

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。