Use to consolidate multiple already-run judge verdicts into one report — consensus, conflicts, must-fix/should-fix with per-judge provenance. Consume-only, no opaque score, never auto-gates.
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。
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概要と使いどころ
Use to consolidate multiple already-run judge verdicts into one report — consensus, conflicts, must-fix/should-fix with per-judge provenance. Consume-only, no opaque score, never auto-gates.
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。
Coordination guidance for the narrow case of multiple desktop-backed agents active concurrently in the same desktop-backed coordination context. Use ONLY when two or more desktop peers are running at the same time; normal CLI agents and single desktop peers should ignore this skill. Read this BEFORE concurrent desktop-to-desktop handoffs to keep sender labels unique, identity routing cooperative, and material handoffs proven.
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。
Multiple agents draft a structured document through federated co-authorship and formal voting.
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。
Combine independent work from two or more selected agents into one decision-ready research report, design, or proposal. Preserve useful complementary findings, develop stronger combined options, and present material alternatives only when they exist. Use when multiple perspectives should improve the product without forcing consensus or staging disagreement.
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, update, validate, and package Canvas Plugins. Use when users want to build a Canvas plugin, bundle multiple skills into a plugin, define plugin metadata, add icons or logos, declare recommended Composio, Canvas Email, or MCP connectors, prepare a marketplace entry, or submit a plugin to the Canvas Plugin Store.
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 reading, writing, or watching the macOS clipboard — NSPasteboard types and multiple representations, the changeCount polling pattern, the transient/concealed pasteboard conventions clipboard tools must respect, and the Sequoia paste-privacy alerts.
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。
Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
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。
Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.
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。
Produce comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.
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。
Posts content to WeChat Official Account (微信公众号) via API or Chrome CDP. Supports article posting (文章) with HTML, markdown, or plain text input, and image-text posting (贴图, formerly 图文) with multiple images. Markdown article workflows default to converting ordinary external links into bottom citations for WeChat-friendly output. Use when user mentions "发布公众号", "post to wechat", "微信公众号", or "贴图/图文/文章".
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 image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
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。
GStack design-shotgun method for rapidly exploring multiple distinct design directions before choosing one to implement or polish.
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。
Rules, conventions, and constraints for formatting git commit messages and committing at logical boundaries. Trigger when: - Drafting, revising, or validating git commit messages. - Pausing at commit boundaries under the CORE or CONTINUE workflows. - Evaluating whether a changeset should be split into multiple commits. - Prompt contains keywords: commit message, git commit, conventional commits, commit hygiene, commit guidelines, logical boundary, spaghetti diff, atomic commit, commit boundary.
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。
Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.
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。
Download an entire website as local files — markdown, screenshots, or multiple formats per page. Use this skill when the user wants to save a site locally, download documentation for offline use, bulk-save pages as files, or says "download the site", "save as local files", "offline copy", "download all the docs", or "save for reference". Combines site mapping and scraping into organized local directories.
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。
Bulk extract content from an entire website or site section. Use this skill when the user wants to crawl a site, extract all pages from a docs section, bulk-scrape multiple pages following links, or says "crawl", "get all the pages", "extract everything under /docs", "bulk extract", or needs content from many pages on the same site. Handles depth limits, path filtering, and concurrent 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。
Extract clean markdown from any URL, including JavaScript-rendered SPAs. Use this skill whenever the user provides a URL and wants its content, says "scrape", "grab", "fetch", "pull", "get the page", "extract from this URL", or "read this webpage". Handles JS-rendered pages, multiple concurrent URLs, and returns LLM-optimized markdown. Use this instead of WebFetch for any webpage content 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。
Use when work is ambiguous or has multiple viable paths; compares options, assumptions, evidence, tradeoffs, and the best next 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。
Prove a Convex feature works — seed, drive as multiple mocked users via convex-test, assert behavior including the negative authz cases (wrong user refused, data-scope enforced).
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。
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
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。
Project workflow for PRDs, task tracking, changelog sync, and documentation updates. Use for any non-trivial task that spans multiple steps, touches several files, changes architecture, or needs project tracking updates. Also activates with @update to sync task.md, changelog.md, and files.md after completing 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。
Project workflow for PRDs, task tracking, changelog sync, and documentation updates. Use for any non-trivial task that spans multiple steps, touches several files, changes architecture, or needs project tracking updates. Also activates with @update to sync task.md, changelog.md, and files.md after completing 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。
Prove a Convex feature works — seed, drive as multiple mocked users via convex-test, assert behavior including the negative authz cases (wrong user refused, data-scope enforced).
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。
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
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。