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Edit English prose to remove repetitive AI phrasing, inflated language, and mechanical structure while preserving meaning and the author's voice. Use for requests to humanize, de-slop, rewrite naturally, or fix tone. Also compose from the author's English notes or transcripts and ask targeted questions when real details are missing. For Brazilian Portuguese, use the companion humanizar skill.

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 well-structured agent loops with best-practice coaching and cross-model review gates before you run them. Use when the user wants to design, build, or set up an agent loop, iterative agent workflow, self-review loop, LLM-as-judge loop, multi-model council, reviewer/judge gate, or goal-driven looping process. Guides goal refinement, typed verification criteria, reviewer/judge selection, privacy boundaries, termination guards, and observability, then emits a RUN_IN_SESSION.md handoff prompt plus portable loop.yaml, loop.resolved.json, LOOP.md, and run-loop.py.

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 a short motion-graphics video ad — a 15s Facebook/Instagram/TikTok spot — as a rendered MP4. Researches the destination landing page so every on-screen claim matches it, pulls real product imagery off the live site, animates one paused GSAP timeline in a single HTML page, and renders it frame-accurately through Playwright and ffmpeg. Use this whenever the user wants a video ad, promo video, animated ad, "an ad for my product", Meta/TikTok/Reels creative in video form, a 9:16 or 1:1 cut of an existing spot, or a re-render of an earlier ad with a different hook, hero or CTA — including when they never say the words "motion graphics". Not for animating UI inside an app, not for static image ads, and not for long-form or voiceover-led video.

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。

Automated iterative agent runner for spec-based development in Kiro. Wraps kiro-cli in a self-correcting bash loop that picks up tasks from a Kiro spec, implements them one at a time, verifies against exit criteria, and accumulates corrections and codebase patterns across iterations. Use this skill when the user mentions "ralph loop", "ralph", "spec loop", "iterative spec runner", "run my spec tasks automatically", "kiro spec automation", "self-correcting agent loop", "implement spec tasks in a loop", "run kiro-cli in a loop", "automated task implementation", or wants to drive a Kiro spec to completion through repeated agent iterations. Also use when the user wants to set up, configure, troubleshoot, or understand the Ralph Loop workflow — including progress tracking, corrections, codebase patterns, timing logs, and the summary 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。

Evaluate any agent skill against a merged framework — Anthropic's Claude Code best practices plus Matt Pocock's writing-great-skills methodology — across 4 axes (Trigger, Structure, Steering, Pruning). Produces an evidence-cited scorecard (0–100), a weighted overall score, and diagnosed failure modes with prioritized fixes. Use when the user asks to evaluate, rate, or audit a skill ("evaluate this skill", "skill scorecard", "review SKILL.md"), or to compare two 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 creating, formatting, or optimizing content for a Substack newsletter. Covers post structure, SEO metadata (titles, slugs, meta descriptions), native engagement features (Notes, Polls, Chat), monetization tactics, and free-to-paid conversion 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。

Sub-skill: Implement ARD (Agentic Resource Discovery). Publish /.well-known/ai-catalog.json so agents can discover MCP servers, A2A agents, skills and API tools (agenticresourcediscovery.org / ai-catalog).

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。

Sub-skill: Implement Auth.md for agent registration discovery. Serve /auth.md with OAuth metadata at /.well-known/oauth-protected-resource and authorization server endpoints.

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。

Sub-skill: Implement DNS-AID records so agents discover endpoints through DNS. Use SVCB/HTTPS records under _agents namespace with alpn and connection parameters.

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。

Sub-skill de agent-ready-cloudflare: Implement MCP Server Card

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。

Sub-skill: Scan any URL for agent readiness. Checks 22 standards across 5 categories, returns readiness level (0-5), status of all checks, and fix instructions.

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 improve website readiness for AI agents using the Cloudflare "Is It Agent Ready?" scanner (isitagentready.com). Covers scanning via API, interpreting results, generating implementation prompts, and fixing every check. Use when the user mentions "agent ready", "isitagentready", "AI agent scan", "agent readiness", "agent-ready score", "MCP server card", "agent skills index", "markdown for agents", "content signals", "web bot auth", "agent discovery", "RFC 9727", "RFC 8288", "RFC 9728", "SEP-1649", "WebMCP", "ARD", "ai-catalog", "x402", "UCP", "ACP", or wants to make a website discoverable and usable by AI agents.

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 skill for building, migrating, and maintaining Astro v7 projects. Covers best practices from the official AGENTS.md, the v6→v7 migration path, validation of breaking/deprecated patterns, AI-enhanced dev server usage (background mode, JSON logging), advanced routing with src/fetch.ts, route caching, Sätteri Markdown, and the Rust compiler. Use when the user mentions 'Astro', '.astro files', 'astro dev', 'astro build', 'islands architecture', 'content collections', 'SSG', 'SSR adapter', 'upgrade to Astro 7', 'migrate Astro', 'Astro v7', 'Astro v6', 'Sätteri', 'route caching', 'Astro.cache', 'astro dev --background', 'src/fetch.ts', 'advanced routing', 'Hono + Astro', 'Rolldown', 'Vite 8', 'queued rendering', 'CDN cache provider', 'Astro AI', 'related content', 'related posts', 'vector embeddings Astro', 'astro-related-content', or asks about static site generation with Astro.

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, validate, and explain `auth.md` files — the open protocol for AI agent registration. Use when making apps agent-ready, generating Protected Resource Metadata (RFC 9728), validating auth.md files, or implementing agent registration endpoints. Triggers on "auth.md", "agent registration", "agent auth", "make my app agent-ready", "ID-JAG", "identity_assertion", "service_auth", "protected resource metadata", "agentic registration".

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 Coolify operator for self-hosted deployment platform. Use when the user mentions 'coolify', 'deploy on coolify', 'list/restart/redeploy applications', 'view coolify logs', 'coolify API/CLI', 'manage coolify servers/databases/apps', or 'coolify context'. Automates deployments and management via REST API or official CLI.

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。

Validate DESIGN.md files against the official Google specification using the `@google/design.md` CLI linter. Works with local files. Use when the user wants to lint a DESIGN.md, check spec compliance, find broken token references, verify WCAG contrast ratios, diff two versions, export tokens to Tailwind or DTCG format, or audit a design system file for structural correctness. Trigger on mentions of "validate DESIGN.md", "lint DESIGN.md", "check my design.md", "design.md spec compliance", "WCAG contrast check", "broken token references", "design token validation", "export design tokens", "diff design systems", "design.md audit", "@google/design.md", "npx design.md lint", "design system validation", "frontmatter tokens", or any request to verify a DESIGN.md 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。

Optimize content for AI-generated responses and LLM citations (ChatGPT, Perplexity, Google AI Overview, Claude, Gemini). Use when the user mentions 'GEO', 'AEO', 'AI SEO', 'LLM optimization', 'citation rate', 'AI visibility', 'optimize for ChatGPT', 'roundup pages', or wants to audit pages for AI discoverability. Includes terminology alignment, FAQ schemas, and community signal 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。

Reescreve textos em português brasileiro para soarem mais humanos e naturais, reduzindo padrões típicos de escrita gerada por IA sem alterar fatos, argumento ou intenção. Use quando o texto em PT-BR parecer genérico, burocrático ou gerado por IA, ou quando o usuário pedir para "humanizar", "dar vida", "tirar cara de IA", "remover AI slop" ou "reescrever com voz". Use também para ESCREVER DO ZERO em português qualquer texto que uma pessoa vai assinar ou publicar (post, artigo, e-mail, proposta, release, README, bio, descrição de produto): nesse caso a lista de padrões funciona como filtro de saída. Para textos em inglês, use a skill-irmã `human-ai`. Também trabalha a partir de notas e transcrições do autor e faz perguntas pontuais quando faltam dados essenciais.

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, validate, and enrich Open Knowledge Format (OKF) bundles — the open spec for representing organizational knowledge as markdown files with YAML frontmatter. Use when the user mentions 'OKF', 'Open Knowledge Format', 'knowledge bundle', 'OKF bundle', 'create a knowledge base for agents', 'validate OKF', 'convert to OKF', 'enrich knowledge docs', 'agent-readable knowledge', 'LLM wiki', 'knowledge catalog', 'kcmd', or wants to structure knowledge as markdown files for AI agent consumption. Also use when the user has a directory of markdown files and wants to make them interoperable or conformant with the OKF standard. Even for simple requests like 'make this folder OKF conformant' — the skill has critical structural rules the agent needs.

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 needs to consume the Pier Cloud (Lighthouse) API for cloud cost management — including JWT authentication, listing contexts, workspaces, workspace groups, and FinOps data views. Trigger whenever there is a need to integrate, automate, or debug calls to the Pier Cloud platform via Python, Node.js, or cURL.

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。

Rigorous engineering orchestrator ported from Lauren Tan's pstack (poteto-mode): reads your task, picks one of 23 playbooks (bug fix, feature, refactoring, perf, investigation, prototype, babysit, shipping, autonomous run, orchestrate, and more), routes to bundled procedures (how, why, architect, arena, swarm, interrogate, unslop, technical-writing, show-me-your-work, tdd, and others), and applies 24 engineering principles. Self-contained: no plugin install, no sibling skills required, works with any agent that reads skills.sh-format SKILL.md files. Use whenever a task needs rigor: nontrivial code changes, architecture decisions, debugging, reviews, PRs, long autonomous runs, or "work like poteto", "poteto-mode", "pstack".

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。

Este skill deve ser usado para reescrever currículos com foco em compatibilidade ATS e impacto para recrutadores, e/ou auditar perfis LinkedIn para maximizar visibilidade e conversão profissional. Acionar em pedidos de otimização de currículo, melhoria para ATS, reescrita profissional do CV, adaptação para vaga-alvo, auditoria de compatibilidade ATS, aumento de taxa de entrevista, auditoria de perfil LinkedIn, otimização de headline/about/experiências LinkedIn, análise de SSI, ou alinhamento CV+LinkedIn.

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。

Revenue-Centric Design (RCD) — evidence-backed principles for making a SaaS or startup product convert, retain, and monetize. Use when the user works on a landing page or CRO ("my page isn't converting"), onboarding/activation ("users sign up but don't stick"), churn/retention ("customers keep canceling"), pricing/monetization ("how should I price this"), checkout/forms ("dropdowns kill conversion", "annotated checkout"), dashboards/data viz ("cognitive load", "KPI shortlists"), positioning/ICP/go-to-market, feature scope, A/B-test rigor, or AI-era differentiation — or asks for the behavioral-science mechanism behind a design choice. Also use when another skill needs the principle or evidence behind a conversion/retention/pricing/checkout move. Never apply to gambling, betting, or casino products.

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, score, and compare repositories containing portable Agent Plugins against the official Agent Plugins specification. Use when asked to review a plugin repo, check plugin.json or mcp.json conformance, assess bundled skills and MCP servers, produce an evidence-cited 0–100 plugin scorecard, identify release blockers, or compare two agent plugins side by side.

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。