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概要と使いどころ
Generate synthetic code context for LLM coding tasks. Automatically use this before making code changes, fixing bugs, refactoring, or answering questions about the codebase. Provides execution paths, relevant files, symbols, tests, and code snippets.
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 or extend a dygo Business App using the supported project layout, generators, metadata, SDK, and validation workflow. Use for general app work that is not primarily Entity modeling, access, hooks, Jobs, fixtures, or patches.
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 Sentry issues without copy-pasting stack traces. Uses the Composio CLI to pull issue details, events, breadcrumbs, and suspect commits, then maps the frames to local source so the agent can propose a fix directly.
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。
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
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。
Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.
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。
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
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。
Address GitHub PR review comments and issue feedback using the gh CLI. Fetch all comments, summarize review threads, and apply fixes with explicit user approval.
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。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer
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。
Smart dependency management for any language. Auto-detects project type, applies safe updates automatically, prompts for major versions, diagnoses and fixes dependency 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。
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
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 server-side rendering and hydration in Angular v20+ using @angular/ssr. Use for SSR setup, hydration strategies, prerendering static pages, and handling browser-only APIs. Triggers on SSR configuration, fixing hydration mismatches, prerendering routes, or making code SSR-compatible.
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 or improve Jupyter notebooks iteratively with quality scoring. Arguments: <new|improve|fix> <path> [--topic] [--domain] [--level] [--quality] [--max-iter]
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。
Enrich Jupyter notebooks with pedagogical markdown content. Arguments: [target] [--execute] [--fix-errors] [--strict] [--consecutive] [--iterate]
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。
ALWAYS invoke this skill before writing, editing, generating, or refactoring ANY code. Do not write or modify code directly without first loading and following these Clean Code guidelines. Use when writing new functions/classes, refactoring existing code, reviewing code, fixing bugs, or any task that produces code output.
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。
Auto-activate for polyfactory, ModelFactory, DataclassFactory, MsgspecFactory, AttrsFactory, Use, register_fixture, pytest plugin, __random_seed__, or coverage(). Not for production seeding.
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。
Auto-activate for pytest_databases, Docker DB fixtures, PostgreSQL/pgvector/ParadeDB, MySQL/MariaDB, Oracle/SQL Server, CockroachDB, MongoDB, Redis/Valkey, BigQuery/Spanner, MinIO, or RustFS. Not for mocked DBs.
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。
Preventive hygiene audit of your own Claude Code configuration — memory files, project context (CLAUDE.md), rules, permissions, skills — a deterministic scan of sizes / broken links / stale entries / excessive permissions / junk + interpretation + targeted fixes by agreement. Keeps the setup from rotting before it breaks. Triggers — "check the system", "system health", "workflow hygiene", "what to clean up", "audit memory", "optimize the system".
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 goal loop — give it ONE goal plus how to verify it, the agent runs check→fix→check itself and comes back only with the finished result (code with audit, research with fact-check, content with critique, audit/backtest). Self-verification instead of constant supervision, with hard safety guards. Vary the loop with a verification rubric designed before it runs. Triggers — "work autonomously to the result", "don't come back until it's done", "run the loop yourself", "drive it to done".
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 this skill whenever a task involves running parallel work on a git repository without conflicts — e.g. "fix this bug while I keep working on my feature", "run Claude on two branches at once", "work on this task in isolation", "create a throwaway branch for this experiment", or anything where two agents or sessions might edit the same files. Also trigger when the user asks to use worktrees directly, or when an agent needs its own isolated checkout so it can work without disturbing the main branch. Even if the user just says "do this in parallel" or "don't mess up my current work", consider worktrees.
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。
Trace failing signals through the RTL hierarchy, classify root cause, and write a debug report per issue — no fix is proposed
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 all IP-level testcases from tc_list.md through the bench Makefile, capture results, and write per-failure issue reports with no fix suggestions
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。
Reference when designing autonomous agent systems or deciding agent freedom/safety/context management/collaboration infrastructure. 10 design principles distilled from Karpathy autoresearch (autonomous ML experiment loop) + AgentHub (agent-native Git DAG). Triggered by "autoresearch", "agenthub", "ratchet" ("래칫"), "context budget", "dumb platform", "program.md", "overnight", "autonomous experiment" ("자율 실험"), "branchless", "single-file constraint" ("단일 파일 제약"), "fixed time budget" ("고정 시간 예산") keywords.
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。
Capture durable project or workflow knowledge discovered during work. Use when a mistake, hidden constraint, repeated question, or changed behavior reveals a documentation gap. To root-cause one specific mistake the agent just made and let the user pick fixes, use `learn` (`/learn`) 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。
Checks the canonical upstream issue tracker, discussion forums, and open pull requests, merge requests, or equivalent change queues for existing reports, discussion, or work on a problem just discussed. Use before diagnosing, fixing, or reporting an apparent open-source problem to avoid duplicate effort and missed context.
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。