All Skills

Builds a Power × Interest stakeholder map and generates a communication plan per quadrant. Use when managing a complex launch, aligning cross-functional teams, or preparing stakeholder engagement strategy. Triggers on: stakeholder management, stakeholder map, stakeholder alignment, communication plan, power interest grid, cross-functional alignment, executive alignment, managing up.

Writes X/Twitter threads and single tweets in the user's own voice — the same craft standard as `linkedin-post-writer`, adapted for X's shorter, faster format. Use when drafting an X/Twitter thread, turning an insight into a tweet, or reviewing a thread draft for tone. Normally invoked by `writing-system` once X is the chosen platform, but works standalone too.

Expert product strategy advisor for Senior PMs. Use this skill — proactively and without waiting to be asked — whenever defining a product vision, setting quarterly OKRs, building a roadmap, choosing between competing bets, entering a new product area, or when stakeholders disagree on direction. Also triggers for: "what should we prioritize", "we need a north star", "how do we choose between X and Y", "roadmap conflict", "what are our bets this quarter", "strategy alignment", "choosing what NOT to build", "three bets with trade-offs", "stakeholder misalignment on direction", "product direction for next quarter", "OKR planning". Produces a decision-focused strategy doc: North Star metric, Opportunity Tree, three bets with explicit trade-offs (including do nothing), and a recommended bet with its key assumption.

Expert product analytics advisor for Senior PMs. Use when defining success metrics for a PRD, designing an A/B experiment, setting up an analytics tracking plan, analyzing post-launch impact, or when data exists but there's no clarity on what to measure. Produces structured metrics frameworks that connect to product decisions, not dashboards.

Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy (see `emil-design-eng`). Default to flagging; approval is earned. Use when reviewing a diff for motion quality — not for writing features, fixing unrelated bugs, or general (non-motion) code review. For building an animation from scratch, use `animate`; for a whole-codebase audit, use `improve-animations`. Source: github.com/emilkowalski/skills.

Implementation and taxonomy skill for analytics tracking — event naming, properties, tracking plans, GA4/GTM/Amplitude setup, and debugging. Use this for the "how do we actually wire this up" layer, not the "what should we measure and why" layer (that's `product-analytics` — use this skill alongside it, after the metrics/tracking-plan decisions are made). Use this — without waiting to be asked — whenever the user mentions "set up tracking," "GA4," "Google Analytics," "Amplitude," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "event taxonomy," "are my events firing," "why isn't this event showing up," "naming convention for events," or "instrument this feature." Produces a concrete tracking plan (event names, properties, triggers) plus implementation and debugging steps for the tools actually in use.

Expert prompt optimization system for the prompts INSIDE an AI product you are building — system prompts, LLM feature prompts, chatbot/agent instructions. Use when the user wants to write or improve a system prompt for an AI feature they're shipping, review/critique an LLM prompt, apply prompt-engineering techniques (chain-of-thought, few-shot, structured output, hard constraints) to a product prompt, or optimize cost/latency of a production prompt. Do NOT use this to clarify or structure the user's own vague request to Claude Code — that is `prompt-clarifier`'s job, not this skill's.

Writing standards for any document an AI agent consumes — a skill, a CLAUDE.md/AGENTS.md, or a doc reached by a pointer. Use when creating or editing a skill, or writing/editing CLAUDE.md, AGENTS.md, or any reference doc meant to be read by an agent rather than a human alone.

Expert strategy advisor for products built on LLMs or agents — not general product strategy (see `product-strategy` for that). Use this — proactively and without waiting to be asked — whenever choosing where to apply AI in a product, deciding between RAG and fine-tuning, designing how much autonomy an AI feature should have, evaluating whether an AI feature is actually defensible, or deciding whether to add AI to a feature at all. Also triggers for: "should this be an agent or a simple LLM call", "how much autonomy should this feature have", "RAG vs fine-tuning", "is this AI feature defensible", "our AI feature keeps hallucinating and users don't trust it", "should we build this with AI or just ship it deterministic", "AI product wedge", "what happens to this feature when the models get better", "human-in-the-loop design for AI features". Produces a decision-focused brief: the wedge, the architecture choice, the autonomy level, and the defensibility bet — each with an explicit trade-off.

General GitHub workflow — branching, commits, pull requests, code review, secrets hygiene, submodules, and git worktrees. Use when the user wants to save changes, push to GitHub, open a PR, work with a submodule, set up a worktree, or perform any git/GitHub operation.

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one. Source: github.com/emilkowalski/skills.

Maps the end-to-end customer experience from awareness to advocacy — touchpoints, emotions, friction points, and improvement opportunities per stage. Use when identifying drop-off points, improving onboarding, or understanding the full user lifecycle. Triggers on: customer journey, user journey, journey map, touchpoints, onboarding experience, funnel analysis, churn points, aha moment, drop-off, user lifecycle.

Designs REST and GraphQL APIs following production best practices for resource naming, error handling, versioning, authentication, and documentation. Use this skill when designing new API endpoints, reviewing API contracts, implementing GraphQL schemas, establishing API conventions for a project, or writing API documentation. Apply when creating any route in Next.js API routes or route handlers, any Supabase Edge Function, or any backend endpoint — even if it starts small, these patterns prevent painful rewrites later.

Audits and enforces web interface standards covering accessibility, performance, UX, and code quality from Vercel Engineering's Web Interface Guidelines. Use this skill when reviewing UI code, checking accessibility compliance, auditing design implementations, running pre-merge frontend checks, or when someone asks to "review my UI", "check accessibility", "check my site", "audit design", or "is this component correct". Apply proactively when writing form elements, interactive components, images, animations, or anything that users directly touch — these guidelines prevent common mistakes before they reach production.

Content Publishing Workflow

Enforces a disciplined, evidence-based debugging protocol. Use when the user reports a bug, an unexpected behavior, a broken test, or asks "why is X not working?". Prevents premature fixes and treats symptoms. Blocks code changes until a root cause is confirmed.

Reverse engineering de diseños Figma para generar especificaciones técnicas completas listas para implementar en código. Usar cuando el usuario comparte capturas, exports o descripciones de un diseño en Figma y quiere documentarlo técnicamente, extraer tokens de diseño, entender la estructura de layouts, o preparar una spec para que un desarrollador o Claude Code lo implemente. También usar cuando el usuario dice "reverse engineering del diseño", "documenta este Figma", "quiero implementar este diseño", "dame las propiedades CSS de este diseño", "convierte este diseño a código", o cuando comparte pantallazos de Figma (layers, propiedades, canvas). Activar también cuando el usuario quiere crear documentación técnica de un diseño existente antes de pasarlo a Claude Code.

Maintains a product repo's canonical docs structure (CLAUDE.md, progress.txt, docs/product+system+design-system, context/) as single source of truth, and keeps the log.md session history separate from the progress.txt state snapshot. Trigger after feature completion, before git push, on architecture changes, at session end, or explicit "update docs"/"sync documentation" requests. Skip for trivial changes (<10 LOC, no logic/schema/UI changes).

A library of reusable, production-tested prompt engineering patterns for building AI-powered features. Use when designing system prompts for apps, building AI pipelines, selecting the right prompting technique for a use case, or reviewing prompts for common failure modes. Complements the prompt-engineering skill (which covers the optimization framework); this skill covers the pattern library itself.

Composition Patterns

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use `improve-animations` or `review-animations` instead. Source: github.com/emilkowalski/skills.

Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Fix failing or flaky Playwright tests. Use when user says "fix test", "flaky test", "test failing", "debug test", "test broken", "test passes sometimes", or "intermittent failure".

Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual autoresearch iteration.

Run a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO. Use as the umbrella skill when the user asks for a full SEO analysis or strategy.

Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.

Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

Vector graphics and diagram creation, format conversion (ODG/SVG/PDF) with LibreOffice Draw.

Set up Playwright in a project. Use when user says "set up playwright", "add e2e tests", "configure playwright", "testing setup", "init playwright", or "add test infrastructure".

Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling. Use when the user runs /ar:loop or asks to run an autoresearch experiment continuously on a schedule.

Anti-over-engineering guardrail that activates when an AI coding agent expands scope, adds abstractions, or changes files the user did not request.

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.