Explorar skills

Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).

When the user wants to add or optimize structured data (Schema.org, JSON-LD). Also use when the user mentions "schema," "structured data," "JSON-LD," "rich results," "rich snippets," "Google rich snippets," "featured snippet schema," "add schema to page," "missing structured data," "schema validation error," "Schema Markup Validator," "Google Rich Results Test," "FAQ schema," "Article schema," "Or

Applies multiple testing correction methods including FDR, Bonferroni, and q-value for genomics data. Use when filtering differential expression results, setting significance thresholds, or choosing between correction methods for different study designs.

· Run dev workflow: branch, implement, lint/test, review, docs, PR, merge, release. Triggers: 'start working', 'kick off', 'wrap up', 'ship this', 'ready to ship'. Not for single git ops (use git).

When the user wants to create, plan, or optimize a lead magnet for email capture or lead generation. Also use when the user mentions "lead magnet," "gated content," "content upgrade," "downloadable," "ebook," "cheat sheet," "checklist," "template download," "opt-in," "freebie," "PDF download," "resource library," "content offer," "email capture content," "Notion template," "spreadsheet template,"

End-to-end proteomics workflow from MaxQuant output to differential protein abundance. Orchestrates data import, normalization, imputation, and statistical testing with limma (default) or MSstats for complex feature-level designs. Use when processing mass spectrometry proteomics.

Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inquiry across domains.

Complete 8-phase enterprise software planning cycle for mission-critical systems

· Build/review AI apps: LLMs, RAG, embeddings, agents, evals, local inference. Triggers: 'llm', 'rag', 'embedding', 'openai sdk', 'agent loop', 'fine-tune', 'ollama', 'vllm'. Not for MCP (use mcp).

Escreve e depura diversos tipos de testes, como unitários, de integração, E2E, TDD, mocks, fixtures, acessibilidade e performance. É acionado por termos como 'test', 'spec', 'TDD', 'playwright', 'vitest', 'jest', 'pytest', 'coverage' e 'flaky', mas não é para testes de segurança.

Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, scree

프리런치 체크리스트 + 단계적 롤아웃 전략. 배포 전 품질 게이트, 모니터링 설정, 롤백 계획을 체계적으로 점검. "런치", "배포 준비", "출시 체크리스트", "go-live" 요청에 실행. /launch로 실행.