skills

Planeja, cria, distribui e monetiza conteúdo no Instagram combinando duas metodologias complementares — Hyeser (criador tático — Reels, viralização, engajamento, faceless) e Rafael Kiso (fundador da mLabs — algoritmo como grafo, retenção por superfície, busca/SEO/IA, jornada do consumidor, social media como negócio). Aciona ao definir nicho/subnicho, bio, @nome e plano 0→1000; montar estratégia de conteúdo (matriz COCA intenção×jornada); roteirizar Reels com gancho/retenção; planejar Stories, cadência e horário; diagnosticar alcance/engajamento/shadowban/Turbinar; otimizar busca, legenda-SEO, aparição em IA (AEO) e hashtags; planejar monetização (afiliado, cortes, faceless, Instagram Shop, venda pelo Direct, infoproduto) e precificação/agência/UGC. Usa o motor de retenção+sinais sociais por superfície e checklists de publicação. Não usar para edição de vídeo em DAW/NLE, geração de imagem por IA, automação/upload via API, nem métricas de YouTube, TikTok ou X (apenas canais de apoio).

Planeja, roteiriza, empacota (título + thumbnail) e otimiza vídeos do YouTube combinando duas metodologias complementares — Escola Para Youtubers (Caique Pereira — embrulho-primeiro, algoritmo, CTR) e Camilo Coutinho (veterano ~20 anos — SEO de busca/Google, sistema de produção sustentável, decisões de canal) — validadas por métricas reais de múltiplos canais. Aciona ao definir ideia/ângulo/nicho, gerar títulos e conceitos de thumbnail, escrever roteiro com gancho de retenção, diagnosticar CTR/retenção/algoritmo/SEO, otimizar descrição/capítulos/playlists, planejar monetização e crescimento (YouTube Shopping, YPP, Brand Connect, Shorts, copyright), montar sistema de conteúdo ("Fortaleza de Vídeos") e decidir nome/recomeço/migração de canal. Usa a pirâmide embrulho-primeiro, o funil de cinco etapas e checklists de publicação. Não usar para edição de vídeo, geração de imagem por modelo de IA, upload via API, métricas de TikTok, Instagram ou X, nem para parecer jurídico definitivo de direitos autorais.

Creates and maintains Knowledge Base topics from YouTube channels by scaffolding a yt-channels topic, bulk-ingesting transcripts through kb ingest channel, and validating/indexing the result. Use when turning a YouTube channel into a Karpathy KB topic. Do not use for single-video ingestion, general video summaries, or non-YouTube sources.

Runs an optional cross-LLM peer review of an implemented change (the diff) via `compozy exec` and requires the reviewer to write one scoped Markdown findings artifact for user-directed remediation. The reviewer runtime is configurable through --ide / --model / --reasoning (defaults claude / opus / xhigh) and the verification gate through --verify. Project-agnostic: works in any repo and any language, auto-discovers project rule files (CLAUDE.md, AGENTS.md, .cursor/rules, CONTRIBUTING.md), auto-detects the verify command, and writes artifacts to --out, an auto-detected .compozy/tasks/<slug>/qa/ layout, or a .peer-reviews/<timestamp>/ fallback. Use after any implementation pass (feature, bug fix, refactor) when the user explicitly asks for an external review of the diff before commit or PR. Do not use for spec/TechSpec review (use spec-peer-review), automatic remediation, or auto-looped review cycles.

Runs an optional cross-LLM peer review of a spec (TechSpec, design doc, RFC, or detailed PRD) via `compozy exec` and requires the reviewer to write one scoped Markdown findings artifact for user-directed incorporation. The reviewer runtime is configurable through --ide / --model / --reasoning (defaults claude / opus / xhigh). Project-agnostic: works in any repo, auto-discovers project rule files (CLAUDE.md, AGENTS.md, .cursor/rules, CONTRIBUTING.md), and writes artifacts to --out, an auto-detected .compozy/tasks/<slug>/qa/ layout, or a .peer-reviews/<timestamp>/ fallback. Use when a spec draft has already been approved by the user and they want an external review round, especially for autonomy/network/security/migration-impacting designs. Do not use for implementation/diff review (use impl-peer-review), automatic approval gates, or auto-looped review cycles.

Control cmux panes and surfaces to coordinate terminal agent workers. Use when a top-level agent needs to launch, prompt, monitor, or manage Claude Opus and Codex GPT-5.5 TUIs in the current cmux workspace, track worker state, delegate bounded tasks, or verify worker reports.

Guides a founder through the full Y Combinator batch application end-to-end. A 10-phase workflow that captures the live YC form, profiles the founders, stress-tests the idea via an embedded grill loop, runs a mandatory 5-agent parallel external research pass on the startup, drafts every form field with anti-pattern and accepted-example checks, produces founder-video bullet notes (no script), runs a final adversarial gate, generates paste-ready submission answers, unlocks an interview-prep simulator after invite, and supports reapplicant delta tracking and post-decision post-mortems. Writes a documented markdown trail under a user-chosen workspace. Use when a founder wants to prepare a YC batch application, build their founder video, drill mock YC interview questions, or reapply with delta evidence. Don't use for pitch-deck design unrelated to YC, generic startup advice without applying, or post-funding work.

Authors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.

Dispatches scoped-write explorer agents in parallel for general research and exploration of any codebase, topic, or domain. The operator passes --path (output directory), --agents (parallel count), --prompt (research question), and optionally --ide, --model, --reasoning to control the Compozy runtime. The parent scouts the territory first to divide work, then invokes `compozy exec --agent explorer` N times in parallel (via the harness's async/background facility); each invocation writes one analysis file at <path>/analysis/NN_analysis_<slug>.md following a seven-section schema. The parent then synthesizes <path>/analysis/summary.md. The explorer agent lives in the Compozy global registry at ~/.compozy/agents/explorer/AGENT.md and is installed by the bundled script when absent. Use when running parallel multi-area research that must produce written artifacts. Do not use for competitor-only research already covered by cy-research-competitors, single-file lookups answerable by Explore, or edits to existing code.

Audits AI-implemented work for honest completion. Runs independent-evaluator checks against task artifacts, transcripts, tests, CI evidence, requirement-to-test mapping, status front matter, and quality gates; flags skipped tests, weakened assertions, mock-only confidence, snapshot drift, happy-path-only coverage, flaky retries, and status/evidence mismatches. Use when validating completed Compozy tasks, AI-authored PRs, or codex-loop iterations. Do not use for real-user QA, persona/journey testing, exploratory charters, or product usability sessions; use qa-execution for those.

Guides creation and modification of domain feature systems organized under a systems/ directory. Covers directory layout, API service layer patterns, TanStack Query hooks (queries, mutations, optimistic updates), React context and XState store conventions, hook organization, and public API barrel exports. Use when adding a new domain system, extending an existing one, or fixing bugs in a system-layer codebase. Don't use for generic React component work, backend API implementation, or codebases not organized around a systems/ domain pattern.

Deep architectural audit focused on finding dead code, duplicated functionality, architectural anti-patterns, type confusion, and code smells. Use when user asks for architectural analysis, find dead code, identify duplication, or assess codebase health. Don't use for style/formatting issues, performance profiling, security audits, or feature-level code review.

Build terminal user interfaces with Go and Bubbletea framework. Use when creating TUI apps with the Elm architecture, dual-pane layouts, accordion modes, mouse/keyboard handling, Lipgloss styling, and reusable components. Includes production-ready templates, effects library, and battle-tested layout patterns from real projects. Don't use for plain-text CLI scripts without an interactive UI, web/desktop GUIs, or non-Go terminal frameworks (Ink, Textual, Ratatui).

Orchestrates multi-advisor council debates on high-impact architecture, technology, or product decisions. Dispatches 3-5 domain archetype subagents (pragmatic-engineer, architect-advisor, security-advocate, product-mind, devils-advocate, the-thinker) through opening statements, tensions, position evolution, and synthesis phases. Preserves dissent and delivers actionable recommendations with captured risks. Use when evaluating trade-offs, stress-testing a PRD or tech spec, resolving dilemmas with multiple viable options, or when a decision needs diverse expert perspectives. Don't use for simple yes/no questions, factual lookups, creative brainstorming without tradeoffs, or tasks where a single expert perspective suffices.

Production-safe Drizzle migration workflow for schema changes that require data backfills or constraint tightening. Use when changing enums/check constraints/defaults, removing status values, or sequencing custom and generated migrations in Drizzle. Trigger on requests about Drizzle migration safety, deployment-safe backfills, migration ordering, and rollback planning. Don't use for ORMs other than Drizzle, app-layer query optimization, or greenfield schema design.

End-to-end remediation workflow for PR review feedback by PR number. Use when Codex must export CodeRabbit issues for a PR, fix every issue completely, commit all fixes in a single commit, and resolve GitHub review threads afterward. Don't use for general PR reviews unrelated to CodeRabbit, draft PRs without review threads, or merge-strategy decisions.

Intelligently handle git rebase operations and resolve merge conflicts while preserving features and maintaining code quality. Use when rebasing feature branches, resolving conflicts across commits, and ensuring clean linear history without losing changes. Don't use for merge-commit workflows, cherry-picking individual commits, or initial repository setup.

Enforce root-cause fixes over workarounds, hacks, and symptom patches in all software engineering tasks. Use when debugging issues, fixing bugs, resolving test failures, planning solutions, making architectural decisions, or reviewing code changes. Activates gate functions that detect and reject common workaround patterns such as type assertions, lint suppressions, error swallowing, timing hacks, and monkey patches. Don't use for trivial formatting changes or documentation-only edits.

Transform outside-of-diff review files into properly formatted issue files for a given PR. Use when converting review files from ai-docs/reviews-pr-<PR>/outside/ into issue format in ai-docs/reviews-pr-<PR>/issues/. Automatically determines starting issue number and preserves all metadata (file path, date, status) from original review files. Don't use for inline-diff review files, non-PR review artifacts, or creating GitHub issues directly.

Executes real-user QA sessions through public interfaces using personas, journeys, exploratory charters, test tours, edge-case probes, CFR checks, and browser evidence. Reads qa-report artifacts from <qa-output-path>/qa/ when present, captures issues/screenshots/reports under the same output tree, and classifies bugs by user impact. Use when validating a release candidate, migration, refactor, or user-facing change against production-like behavior. Do not use for AI implementation audits, task-status reconciliation, CI gate runs, integration/security/performance templates, or flaky-test triage; use agent-output-audit for those.

Plans real-user QA deliverables: personas, journey maps, exploratory charters, persona/journey/tour/CFR test cases, regression suites, Figma validation checks, automation intent, and user-impact bug reports. Writes artifacts under <qa-output-path>/qa/ for qa-execution to consume. Use when planning QA before execution, documenting journey-driven test strategy, marking flows that need E2E follow-up, or filing structured bug reports. Do not use for live execution, AI implementation audits, CI gate ownership, or technical integration/security/performance suites; use qa-execution or agent-output-audit instead.

Comprehensive React development guide covering component architecture, hooks, state management, TypeScript integration, useEffect patterns, and testing with Vitest. Use when creating React components, custom hooks, managing state, or any frontend React code. Essential for React 19+ development. Don't use for React Native, non-React frameworks (Vue, Svelte, Solid), or backend-only Node.js code.

Analyzes codebases to identify refactoring opportunities based on Martin Fowler's catalog of code smells and refactoring techniques. Detects duplicated code, high coupling, complex conditionals, primitive obsession, long functions, and other structural issues. Produces a structured refactoring report with prioritized findings saved to docs/_refacs/. Use when auditing code quality, preparing for a refactoring sprint, or reviewing architectural health. Don't use for style/formatting issues, performance optimization, or security audits.

Comprehensive Rust coding guidelines covering ownership, error handling, async patterns, traits, testing, performance, clippy, and documentation. Use when writing new Rust code, reviewing or refactoring existing Rust, implementing async systems with Tokio, designing error hierarchies, choosing between borrowing and cloning, setting up tests or benchmarks, configuring linting, or optimizing performance. Do not use for non-Rust languages or general software architecture unrelated to Rust idioms.

Ships a finished feature, bug fix, or refactor end-to-end — explores the change's impact on docs/site/README, generates release notes (via pr-release if present, otherwise inline from git log), writes a complete PR description (including QA screenshots and summary when qa-report/qa-execution artifacts exist), commits staged changes following the repo's commitlint config, opens the PR via gh CLI, and optionally launches a CodeRabbit review watch loop. Use when a feature/bug/refactor is implementation-complete and ready to ship. Do not use for draft PRs without finished work, for amending an already-merged PR, for repo-level release publishing (use pr-release directly), or for in-progress development checkpoints.

Authors and structures professional-grade agent skills following the agentskills.io spec. Use when creating new skill directories, drafting procedural instructions, or optimizing metadata for discoverability. Don't use for general documentation, non-agentic library code, or README files.

Diagnoses and refactors existing SKILL.md files whose references or assets are ignored by agents. Applies Required Reading Routers, hard STOP directives, gist-tripwire trimming, and flat one-level reference structures so bundled context is loaded deliberately. Use when auditing or rewriting long skills that feel shallow despite deep reference files. Do not use for authoring new skills from scratch, non-skill Markdown, or documentation without SKILL.md front matter.

Create, update, or refactor Storybook stories following the project's standard patterns. Use when adding stories for new components, updating existing stories, or fixing Storybook-related issues. Don't use for component implementation itself, design-system token changes, end-to-end browser tests, or non-Storybook documentation.

Guide for Tailwind CSS v4 patterns and best practices. Use when styling components with Tailwind CSS, creating responsive layouts, or working with Tailwind 4 features. Don't use for plain-CSS authoring, CSS-in-JS libraries (styled-components, emotion), or non-Tailwind utility frameworks.

Comprehensive guide for the TanStack ecosystem in React — Query (caching, mutations, prefetching, SSR), DB (collections, live queries, optimistic updates), Form (state, validation, fields), Router (file-based, type-safe navigation, search params, loaders), and Start (server functions, middleware, auth, SSR). Use when working with any TanStack library in a React/full-stack project. Don't use for non-TanStack data libraries (SWR, Apollo, RTK Query), non-React TanStack ports (Solid, Svelte), or backend-only work.

Install official tech brand logos from the Elements registry. Use when user needs logos for tech companies (Clerk, Vercel, GitHub, etc.), AI providers (OpenAI, Anthropic, Claude), social platforms, or any brand assets. Triggers on "logo", "brand", "icon for [company]", "add [company] logo", placeholder logo detection, or when building landing pages, auth UIs, or integrations showcases. Don't use for custom in-house logos, generic icon libraries (Lucide, Heroicons), or marketing image assets.

Comprehensive testing doctrine for software and AI systems — covers positive patterns, anti-patterns, gates for coding agents writing tests, CI discipline, and an LLM/agent evaluation primer. Use when authoring or reviewing tests, adding mocks, deciding test placement, generating tests via agents, debugging flaky CI, designing eval suites for LLM features, or rebuilding a brittle test suite. Contains 12 positive patterns (selector hierarchy, table-driven, builders, real-system gates), 25 anti-patterns across Brittleness, Flakiness, Mock-misuse, Process, and AI-specific families, 7 mandatory gates for agents writing tests, flaky-test taxonomy with quarantine workflow, contract / property / mutation testing patterns, and an oracle-ladder primer for LLM-as-judge and agent eval. Language-agnostic — pseudo-code only. Don't use for general code review, library-specific debugging unrelated to tests, non-testing CI pipeline design, or production observability.

Transform code, issues, or context into a detailed prompt/context for another LLM to fix or implement. Use when preparing comprehensive context for external LLM assistance, bug fixes, improvements, or feature implementations. Provides detailed context without implementation suggestions, letting the receiving LLM decide how to implement solutions. Focuses on "what" (problem, requirements, current state) not "how" (implementation approach). Don't use for prompts that already prescribe an implementation, simple one-shot questions, or end-user-facing copy.

Uses the TweetSmash REST API to fetch bookmarks, inspect labels, and add or remove labels from saved tweets. Use when integrating TweetSmash into scripts, agents, workflows, cron jobs, or internal tools that need bookmark retrieval, filtering, pagination, or label management. Do not use for direct browser automation inside TweetSmash, unrelated X or Twitter APIs, or tasks that only need product marketing copy.

Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects. Don't use for plain JavaScript, runtime validation libraries (Zod, Yup), or basic TypeScript syntax questions.

Provides guardrails for user-facing UI work: usability heuristics, accessibility floors, design-system discipline, component states, microcopy, motion, dark mode, responsive behavior, and human-AI UX. Use when designing, generating, reviewing, or refactoring visible product surfaces such as components, pages, dashboards, forms, dialogs, loading/empty/error states, or AI interfaces. Do not use for backend-only work, infrastructure, CLI/TUI design, or pure documentation editing.

Comprehensive guide for XState v5 ecosystem including state machines, actors, @xstate/store, and TanStack Query integration. Use when implementing state machines, event-driven stores, client state management, or integrating XState with React and TanStack Query for data fetching orchestration.

Generates 150-750+ ad variations using Alex Hormozi's combinatorial Hook x Meat x CTA framework. Triggers on requests to create ads, ad copy, ad scripts, marketing creatives, video ad scripts, ad hooks, CTAs, ad testing, ad scaling, or ad factories. Also triggers on mentions of Hormozi's ad method or combinatorial ad creation. Does not trigger for general copywriting, email marketing, landing pages, or non-advertising content.

Centrifugo real-time messaging server expert for WebSocket PUB/SUB, channel management, JWT authentication, event proxying, and horizontal scaling with Redis/NATS. Use when: centrifugo, centrifugal, real-time messaging, websocket pubsub, channel subscriptions, real-time notifications, live updates, presence, history recovery, server-sent events integration, real-time transport layer. Do not use for: general WebSocket programming without Centrifugo, Socket.IO, Pusher SDK, or other real-time frameworks.

Comprehensive guide for electron-builder (v26.x) packaging, code signing, auto-updates, and release workflows. Use when: (1) configuring electron-builder builds (electron-builder.yml or config.js/ts), (2) setting up macOS/Windows code signing or notarization, (3) implementing auto-updates with electron-updater, (4) publishing to GitHub Releases, S3, or generic servers, (5) configuring platform targets (NSIS, DMG, AppImage, Snap, PKG, MSI), (6) working with build hooks (beforePack, afterSign, afterAllArtifactBuild), or (7) using the programmatic API. Triggers on: electron-builder, electron-updater, code signing, notarize, NSIS, DMG, AppImage, auto-update, publish releases, build hooks, electron packaging, electron distribution.