Use when reviewing active Loop Factory specs against the working tree, checking verification evidence, deciding ACCEPTED or CHANGES_REQUESTED, and archiving accepted specs.
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。
1.4万 件 ・ 関連度順
概要と使いどころ
Use when reviewing active Loop Factory specs against the working tree, checking verification evidence, deciding ACCEPTED or CHANGES_REQUESTED, and archiving accepted specs.
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。
Comprehensive Mastra framework guide. Teaches how to find current documentation, verify API signatures, and build agents and workflows. Covers documentation lookup strategies (embedded docs, remote docs), core concepts (agents vs workflows, tools, memory, RAG), TypeScript requirements, and common patterns. Use this skill for all Mastra development to ensure you're using current APIs from the installed version or latest 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。
Work with Runpod GPU infrastructure and documentation. Use when Codex needs to create, deploy, manage, debug, or review Runpod Pods, Serverless workers/endpoints, templates, network volumes, Public Endpoints, Flash apps, runpodctl commands, Runpod Python SDK usage, REST/GraphQL API usage, Runpod MCP setup, Docker images for Runpod, endpoint request payloads, logs, billing/cost checks, or Runpod deployment troubleshooting.
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。
Mechanical documentation hygiene. Spawns a doc-maintainer agent to audit all project documentation and fix correctness, completeness, freshness, and consistency issues autonomously within its authority. Surfaces anything requiring user judgment for 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。
Mechanical git repo hygiene. Prunes stale remote-tracking refs, deletes merged local branches (with confirmation), and reports stashes, untracked files, and unpushed work. Never touches remote state. Safe by default — destructive operations require explicit operator 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。
Adversarial project planning workflow. Explores the problem space, drafts tickets in batches, then runs sequential adversarial loops — a mandatory UX loop ("should we build this?"), zero or more discretionary specialist loops (security, performance) for projects with architectural implications in those domains, and a mandatory implementer loop ("could we build this?") — to find gaps before implementation. Creates well-specified, batch-tagged tickets upstream only after every applicable loop signs off.
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 when debugging runtime behavior requires live data from the running app, temporary instrumentation, or hypothesis verification through logs. Trigger for async timeouts, stale or incorrect state updates, race conditions, event ordering bugs, intermittent failures, browser/client behavior that static inspection cannot explain, or any issue where the agent should create a local debug HTTP server, insert temporary probes, ask the user to reproduce, inspect .debug/debug.log, then remove all debug instrumentation and assets.
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 natural-language image requests and rough prompts into ready-to-use GPT Image 2.5 prompts using the official prompting guide as a live reference. Use when users ask to improve image prompts, 优化生图提示词, 把想法变成提示词, or write prompts for GPT Image 2.5 Flare or Sunburst. Produces prompt text, not images, unless the user explicitly asks to generate.
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。
AI media generation CLI tool using Google's Imagen 4, Veo 3.1, and Gemini TTS. Use when the user wants to (1) generate images from text prompts, (2) edit existing images with AI, (3) explain image contents, (4) generate videos from text or images, (5) create narration/voice audio with character settings. Triggers on requests like "generate an image of...", "create a video...", "make a voice that says...", "edit this image to...", "describe this image".
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 gives a SaaS product's landing page URL, homepage, or name and asks for a full teardown or deep-dive of how the product works across web, desktop, and mobile — including per-platform feature inventories and user journeys, tech stack, pricing/plan mapping, how the platforms integrate and sync (and the business logic behind those choices), hardware integrations, business-scale/revenue signals, and concrete release artifacts per platform — with a structured Markdown report as the deliverable. Trigger on phrases like "research this SaaS", "do a platform teardown of X", "map every feature of this product across web/mobile/desktop", "reverse-engineer how this app works everywhere", or a bare URL plus a request to understand the whole product.
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。
Replace OneCLI gateway with the built-in credential proxy. For users who want simple .env-based credential management without installing OneCLI. Reads API key or OAuth token from .env and injects into container API requests.
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 Agent Swarm (Teams) support to Telegram. Each subagent gets its own bot identity in the group. Requires Telegram channel to be set up first (use /add-telegram). Triggers on "agent swarm", "agent teams telegram", "telegram swarm", "bot pool".
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 local voice transcription instead of OpenAI Whisper API. Switches to whisper.cpp running on Apple Silicon. WhatsApp only for now. Requires voice-transcription skill to be applied first.
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 assessing body fat percentage from skinfold measurements, calculating body density, or interpreting body composition results using Durnin-Womersley or Jackson-Pollock equations.
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 or audit technical text against ASD-STE100 Simplified Technical English so a tired, non-native reader understands it on the first pass: 20-word procedural and 25-word descriptive sentence limits, imperative steps, condition before command, one word for one meaning, and only the approved modals can/will/must. Use for READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, UI copy, and agent instructions. Trigger on: "STE", "Simplified Technical English", "ASD-STE100", "controlled language", "plain English", "make this clearer", "write for non-native readers", "prep this for translation", "cut the fluff", or any request to check text for compliance. Prefer this over general copy-editing whenever the text instructs, documents, or warns.
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 and maintain the learnings in `docs/solutions/` against the current codebase — fix drifted paths and links, merge overlapping docs, replace guidance the code no longer supports, delete obsolete docs, reconcile the `CONCEPTS.md` glossary, then report and commit. Also bootstraps `CONCEPTS.md` on request and, when asked, culls docs whose reasoning the code already explains. Use for "refresh the learnings", "audit docs/solutions", "are our solution docs still accurate", "clean up / prune the learnings", "create a CONCEPTS.md", or after a refactor, rename, migration, or dependency upgrade that likely invalidated documented solutions. Not for capturing a new learning — use `learn-with-docs`.
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。
Resolve CodeRabbit review feedback on a GitHub pull request. Collects every open CodeRabbit finding (inline threads, plus the nitpick and outside-diff findings packed into review bodies), judges and fixes each one against the real code with subagents, unifies fixes that share a pattern, commits locally, asks before pushing, then shows every reply draft linked to its finding and posts only on approval. Runs only on top-tier models. Use on "resolve the CodeRabbit feedback", "address coderabbit comments", "answer the rabbit", "fix what CodeRabbit flagged on
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 for any task involving docstrings, JSDoc/TSDoc, or REST API documentation — even when the request seems handleable without it. Enforces Microsoft contract-first conventions and a bare-minimum rule that Claude won't apply by default: never restate the signature, drop @param/@returns that only echo names and types, always document @throws, and document data shapes as WHAT not WHY. Covers Python docstring styles (Google/NumPy/Sphinx), TSDoc tags and @inheritDoc, and API doc patterns for NestJS/Express/FastAPI/Django. Trigger on: adding or auditing docstrings, redundant or missing tags, deleting comment rot, or producing a documentation-health report. Do not skip for documentation tasks — consistent conventions are the whole point.
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。
Apply this opinionated workflow when reverse-engineering legacy or undocumented systems: scope, explore the code, trace data flows, document in EARS format, flag uncertainties. For code archaeology, onboarding, and requirements extraction.
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 the retrieval recall gate with dead-gold triage and the binary A/B regression test. Required before release tags; use after any retrieval-adjacent 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。
Create a pull request with WSL-safe workflow. Uses --body-file to avoid heredoc permission corruption.
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, rewrite, review, and organize developer-facing documentation for web software projects. Use when creating or improving README files, docs homepages, quickstarts, tutorials, how-to guides, API/reference pages, conceptual explanations, migration guides, or troubleshooting content for frontend, backend, full-stack, SDK, API, or framework-based web products. This skill applies strong information architecture, task-first page structure, clear voice, runnable examples, version and prerequisite hygiene, accessibility rules, and docs-as-code maintenance habits. Do not use it for marketing copy, legal text, or non-technical customer-support articles.
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。
MUST be used for Vue.js tasks. Strongly recommends Composition API with `<script setup>` and TypeScript as the standard approach. Covers Vue 3, SSR, Volar, vue-tsc. Load for any Vue, .vue files, Vue Router, Pinia, or Vite with Vue work. ALWAYS use Composition API unless the project explicitly requires Options API.
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。
FastAPI patterns for async APIs, dependency injection, Pydantic request and response models, OpenAPI docs, tests, security, and production readiness.
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。