2,104 件 ・ 関連度順
概要と使いどころ
Use when the primary outcome is comparing documentation claims with implementation evidence, synchronizing docs from verified changes, or freshness review, including drift, missing coverage, stale claims, and post-change updates.
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。
Routes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only scripting.
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。
Pytest testing patterns for Python — fixtures, behavioral naming, behavior/risk-driven coverage, property-based testing with Hypothesis when useful, and mutation testing when justified. Use when writing tests, designing fixtures, configuring coverage, or applying parametrize, async testing, or property-based 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。
Activates on any Python task involving *.py files, uv, ruff, ty, pytest, or pyproject.toml — loads the shared Python 3.11+ standards and routes the task to the specialist skill that applies them: TDD, CLI, web, data, async, typing, packaging, publishing, documentation sites, test design, test-failure analysis, or stdlib-only constrained environments.
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 CLI applications with Typer and Rich — creating commands with Annotated parameter syntax, defining arguments and options, composing subcommands, async concurrent CLI tasks with semaphores, testing with CliRunner, PEP 723 shebang scripts, progress bars, Rich terminal output, or non-TTY display width handling.
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。
Add automated documentation updater to any Claude skill. Creates a Python sync script that downloads upstream docs, processes markdown for AI consumption, and maintains local cache with configurable refresh. Collects template variables, then delegates implementation through 5-phase workflow. Use when adding auto-updating reference documentation to plugins or 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。
Knowledge reference for Autonomous Refinement Loop research — pattern research into prerequisites for autonomous execution without synchronous human blocking gates. Defines failure categories, prerequisites, and conditions for replacing human judgment with machine-verifiable checks. Use when designing or evaluating autonomous agent loops, gate conditions, or HOOTL execution patterns.
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。
Optimize existing CLAUDE.md, SKILL.md, agent definitions, and other AI-facing files for Claude comprehension and economy. Scope: optimization of existing content only — not upstream sync, not read-only auditing. Measures baseline metrics, delegates to the ai-doc-optimizer agent with file-type-specific context, runs independent verification via second agent, measures post-optimization metrics, and presents comprehensive before/after report. Supports iterative mode for large targets. Use when improving prompt effectiveness, reducing token waste, or rewriting instructions for LLM consumption. Invoke with /optimize-claude-md <file-or-directory>.
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。
Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.
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 TypeScript-specific code review patterns covering strict mode, ESM, type safety, branded types, discriminated unions, async patterns, runtime safety, and common anti-patterns. Activates on detection of tsconfig.json, *.ts, or *.tsx files during code review — loaded automatically by dh:code-reviewer.
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。
DRAFT. Use when running a Luma-centered GTM event campaign: pull/export guests, enrich and score, draft invites and social, stage email+LI sequences paused for approval, and wire registration sync. Not installed by deepline 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。
This skill should be used when the user asks to "add docstrings", "write error handling", "use naming conventions", "handle exceptions", or when writing new Python code for StreamFlow that requires docstring format, naming conventions, exception handling, or async cleanup patterns.
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。
Manage Alibaba Cloud Function Compute (FC) 3.0 using the @alicloud/fc20230330 TypeScript SDK. Use when working with serverless functions on Alibaba Cloud, including function CRUD, invocation, versions, aliases, triggers (HTTP/Timer/OSS/CDN/MNS), async invocation, concurrency and scaling configs, provisioned instances, custom domains, layers, VPC bindings, sessions, and resource tagging. Covers all 67 APIs of the FC 20230330 version.
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。
Manage Alibaba Cloud Container Registry (ACR) Enterprise Edition using the @alicloud/cr20181201 TypeScript SDK. Use when working with container image registries on Alibaba Cloud, including instance management, namespaces, image repositories, image tags, build rules, image synchronization, security scanning, delivery chains, Helm charts, artifact lifecycle, and event notifications. Covers all 115 APIs of the CR 20181201 version.
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。
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend 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。
Nuxt 4 应用模式，涵盖水合安全、性能优化、路由规则、懒加载，以及使用 useFetch 和 useAsyncData 进行 SSR 安全的数据获取。
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。
Write modern, high-performance C# code using records, pattern matching, value objects, async/await, Span<T>/Memory<T>, and best-practice API design patterns. Emphasizes functional-style programming with C# 12+ features.
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。
Publish the octop-memory Python package: cut a release branch from develop, bump version, update CHANGELOG / README, open a PR to main; after merge, Actions tag on main (PyPI + GitHub Release) and sync main into develop. Use when the user asks to publish, release, bump version, cut a release, or run /publish.
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。
Self-hosted skill registry for OpenClaw. Stores procedures your team writes (name, description, body), syncs them to disk before each task, and collects which-helped/which-failed signals from the agent so the registry improves over time.
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。
Show the active SkillNote collection and the skills synced into this project for Codex. Use when the user says "skillnote", "what skills do I have", "show my collection", or wants a SkillNote status/dashboard.
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。
Publish the octop-gateway Python package: cut a release branch from develop, bump version, update CHANGELOG / README, open a PR to main; after merge, Actions tag on main (PyPI + GitHub Release) and sync main into develop. Use when the user asks to publish, release, bump version, cut a release, or run /publish.
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 and query a local Markdown knowledge base ("vault"). TWO functions — (1) CONVERT raw files (PDF, Word/docx, PowerPoint/pptx, Excel/xlsx, csv/tsv, images, html, md/txt, json/yaml/code, audio/video) into clean Markdown with retrieval-friendly frontmatter; local-first (pandoc / python-pptx / openpyxl / pymupdf4llm / whisper), with cloud OCR (MinerU) only as a fallback. (2) ANSWER questions over the resulting vault with retrieval discipline — self-monitor coverage, flag missing/lossy content, and propose Maps-of-Content (MOCs). Triggers: "build/sync my local knowledge base", "convert these files to markdown for AI", "整理我的资料库", "把文件转成 md 给 AI 读", "本地知识库", "读我的本地 vault 回答", "这个主题我的资料里怎么说". Not for: one-off web research, or files that are already in a single doc you can read 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。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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 context manager specializing in information storage, retrieval, and synchronization across multi-agent systems. Masters state management, version control, and data lifecycle with focus on ensuring consistency, accessibility, and performance at scale.
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。