4,664 件 ・ 関連度順
概要と使いどころ
Architecture Decision Records workflow skill. Use this skill when the user needs Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
Architecture Decision Records workflow skill. Use this skill when the user needs Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
Architecture Decision Records workflow skill. Use this skill when the user needs Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
App Builder - Application Building Orchestrator workflow skill. Use this skill when the user needs Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
App Builder - Application Building Orchestrator workflow skill. Use this skill when the user needs Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
Maintaining AGENTS.md workflow skill. Use this skill when the user needs This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
Maintaining AGENTS.md workflow skill. Use this skill when the user needs This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing 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。
Orchestrate a MULTI-PHASE, dependent, or resumable run over many provider subagents from a JS script, off the main context (`cc-fleet workflow`). Use for fan-out→barrier→synthesis, per-item pipelines, loop-until-dry, or a run that must survive a kill and `--resume` from its journal. NOT a flat fan-out of independent tasks (that is /cc-fleet:subagent — cheaper, no script); NOT interactive collaboration (that is /cc-fleet:team); NOT trivial single-shot work for the main session.
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。
Backlink profile analysis: referring domains, anchor text distribution, toxic link detection, competitor gap analysis. Works with free APIs (Moz, Bing Webmaster, Common Crawl) and DataForSEO extension. Use when user says backlinks, link profile, referring domains, anchor text, toxic links, link gap, link building, disavow, or backlink audit.
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 any domain for orphan blog pages, map internal links across all blog posts, generate keyword-backed interlinking briefs via DataForSEO, and produce a self-contained downloadable HTML report. Invoke with the target domain as the argument.
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 and editing for blog content powered by Gemini via MCP. Claude acts as Creative Director - interpreting intent, selecting domain expertise, constructing optimized 6-component prompts (Subject + Action + Context + Composition + Lighting + Style), and orchestrating Gemini for blog-quality results. Generates hero images, inline illustrations, social preview cards, and OG images. Edits existing blog images. Supports 6 blog-optimized domain modes (Editorial, Product, Landscape, UI/Web, Infographic, Abstract). Works standalone via /blog image or internally from blog-write and blog-rewrite workflows. Falls back gracefully when MCP is not configured. Use when user says "blog image", "generate hero image", "blog illustration", "social card", "generate blog image", "edit blog image", "image generate", "blog cover image", "inline image", "OG 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。
Generates a fully structured SEO content **outline** (not a finished brief) and exports it as a formatted .docx Word document. The output is a skeleton for a writer to fill in — section headings, topic prompts, angles — not pre-written paragraphs. Use this skill whenever a user provides a blog title, focus keyword, domain URL, or any combination of those and asks to generate an outline, brief, blog brief, SEO brief, article structure, or content plan. Also trigger when the user says "create a brief for X", "generate an outline for [topic]", "make a content brief", "I need a brief for [URL or keyword]", or pastes a title and asks what the structure should look like. This skill handles input validation, domain analysis, keyword enrichment, audience inference, archetype-aware section selection, and full .docx generation — always use it rather than writing ad-hoc outlines.
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。
Operate ArvanCloud (arvancloud.ir) through its REST APIs, including CDN and DNS records, domains, cache purge, WAF and rate limits, Cloud Server (IaaS v3, v1 and the undocumented v2 backups), Object Storage, Edge Computing, Cloud Container, VOD, Live and Video Ads, plus Let's Encrypt DNS-01 certificates via acme.sh dns_arvan. Use when the user wants to list, create, change or delete anything on ArvanCloud, take an account inventory, find out which account a key belongs to, check quota or usage, or debug an ArvanCloud API error. Also trigger on hosts like napi.arvancloud.ir, ecc.{region}.arvanapis.ir, storage.arvanapis.ir, dejban.arvancloud.ir, an "Apikey" Authorization header, the dns_arvan plugin, or one of the user's ArvanCloud-hosted domains.
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。
Generate and maintain AI-readable markdown documentation for a codebase in docs/. Use this skill whenever the user asks to document their codebase, generate project docs, create architecture docs, update documentation after code changes, build a knowledge base for AI agents, create onboarding docs, map out a codebase, or explain a project structure. Also trigger when users say things like "document this repo", "create docs for my project", "update the docs", "write architecture documentation", "help AI understand my code", "generate a codebase overview", or "maintain docs". This skill is specifically about creating structured markdown files in a docs/ directory that serve as a knowledge base — NOT about writing inline code comments, README files, or API reference docs from docstrings.
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 considered when you need to answer reflow machine maintenance questions or provide detailed guidance based on thermocouple data, MES data or defect data and reflow technical handbooks. This skill covers how to obtain important concepts, calculations, definitions, thresholds, and others from the handbook and how to do cross validations between handbook and datasets.
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 documentation needs creating, checking, or maintaining — docs may have drifted from code, pre-release doc verification, updating docs after finishing code work, adding or enforcing project terminology, deciding where a new doc should live, or a routine re-audit of previously verified 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。
Sync delta specs from a change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change.
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。
Shared review framework that every domain reviewer (pci, oracle, gov, edtech, healthcare, mlops, etc.) MUST follow. Defines the output artifact (TM-{slug}.md), mandatory sections, severity scale, verdict format, the workflow scaffold (when-invoked, Step-0 read-inputs, HANDOFF), and the "domain heuristic vs generic check" boundary. Eliminates duplication across the ~30 reviewer prompts.
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。
Help user buy a domain, configure DNS, set up SSL. Guide every click.
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。
Prepare the desk computer to work with Hyperliquid - install the SDKs, pick testnet or mainnet, verify connectivity, and (only when the user asks) provision a trade-only API wallet through the secure secret store and verify it is approved. Use during desk setup, when moving between research, testnet and mainnet levels, when a key is rotated, or when any Hyperliquid call fails with an environment problem.
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。
Design a Funhouse Mirror activity where students use their own domain expertise to detect AI distortions, omissions, and overconfidence. Use when students know a subject well enough to evaluate AI claims about it.
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。
Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"
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 evidence-first engineering discipline to any agent-built software project: fact discovery before action, evidence-calibrated status reporting, explicit change boundaries and stage gates, controlled confirmation for risky or external actions, sensitive-information redaction for anything shared publicly, and resumable continuity after interruptions. Use when users ask an agent to take over an existing codebase, deliver a feature across stages, verify whether work is actually complete, judge release readiness, or keep conclusions honest about what is proven versus assumed. This foundation skill is domain-neutral; vertical suites (for example mini-program engineering) build on it by adding domain facts and platform rules.
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。
Win #1 Product of the Day on Product Hunt. Completely reverse-engineered from 30x daily winner and 3x weekly winner campaigns — ranking algorithm decoded, launch timing optimized, hunter selection guide, community engagement approach, and post-launch momentum playbook. Use this if you're: (1) already read PH launch guides but still can't break into Top 5 and need algorithm-level deep optimization, (2) targeting Daily #1 and 5,000+ sign-ups with a proven 30+ case validated approach, or (3) an investor/accelerator coaching portfolio companies on PH launches. What's inside: PH ranking algorithm decoded: weighted factors for first 3 hours, 24 hours, and weekly ranking · Pre-launch preparation: gallery optimization, product URL selection, tagline refinement (≤60 chars) · Launch timing optimization: exact PST launch windows + scheduling guide · Community engagement KPIs: upvote targets, comment response time, maker comment strategy · Platform compliance guide: understanding PH's quality signals and organic growth · Post-launch 72-hour plan: maintaining momentum, conditions for Weekly #1 · Case studies: 3 different categories (AI Tool, App, SaaS) dissected Expected outcomes: Product Hunt Daily #1 ranking · strong community engagement on launch day · 3,000–10,000+ sign-ups (depending on product-market fit) 🇨🇳 Product Hunt 打榜完整攻略 | 🇯🇵 Product Hunt ローンチガイド | 🇰🇷 Product Hunt 런칭 가이드 Keywords: Product Hunt #1, Product Hunt launch strategy, PH ranking algorithm, PH #1 daily winner, Product Hunt tips, product launch, startup launch, ranking optimization, PH gallery optimization, Community engagement strategy, maker community engagement, product strategy, launch tactics, how to win Product Hunt, product hunt best practices