glaucia86

Analisa padrões de qualidade de código e detecta code smells, complexidade elevada e duplicação.

Avalia pipelines CI/CD, detectando gaps e oportunidades de melhoria.

Analisa dependências para identificar falta de uso, versões permissivas ou riscos.

Avalia a documentação (README, CONTRIBUTING, etc.) para encontrar lacunas de clareza e onboarding.

Converte achados de outras skills em issues e comentários prontos para o GitHub.

Analisa o perfil do repositório e extrai um modelo estruturado com evidências para orientar outras análises.

Detecta riscos básicos de segurança em repositórios (segredos expostos, configurações perigosas, padrões inseguros) e gera recomendações com evidências.

Faz análise de postura de testes (presença, estrutura, camadas).

Create reveal.js HTML presentations as single-file artifacts. Use this skill whenever the user asks to create a presentation, slide deck, or slides using reveal.js — or when they mention "reveal.js", "revealjs", or want an HTML-based presentation (as opposed to PowerPoint/PPTX). Also trigger when the user wants to convert content (outlines, markdown notes, topics) into a reveal.js deck, or asks to edit/improve an existing reveal.js presentation. This skill covers the full reveal.js feature set: slides, vertical slides, fragments, auto-animate, code highlighting, markdown slides, math (KaTeX/MathJax), backgrounds (color, gradient, image, video, iframe), themes, transitions, speaker notes, layout helpers, lightbox, scroll view, PDF export, the React wrapper (@revealjs/react), and plugin creation. If the user mentions any of these features in the context of presentations, use this skill.

Review a pre-implementation contract or clarification summary as a feedback harness before coding starts. Use when a task already has a clarification artifact and you want a second-pass review of scope boundaries, repository grounding, validation quality, risk coverage, and approval edges before implementation proceeds.

Run a final pre-implementation go or no-go gate after clarification and contract review. Use when a task already has a clarification artifact and, optionally, a contract review verdict, and you want one explicit execution decision: go, go-with-caveats, or no-go before any code changes begin.

Build a pre-implementation harness for ambiguous or risky coding tasks by grounding the request in the repository, producing a structured impact map, surfacing ambiguities and risks, defining scope boundaries, and creating a validation-ready implementation contract before any code changes are made. Use when a task is broad, underspecified, cross-cutting, or likely to drift without an explicit planning checkpoint.

Run a structured four-phase engineering workflow (discovery, implementation, verification, release-readiness) with Human in the Loop checkpoints and explicit go/no-go gates. Use this whenever the user asks for full codebase review before changes, wants QUESTIONS.md-driven implementation, requests validation against approved decisions, or needs a final release gate verdict (Ready, Ready with caveats, Not ready).

Deep critical analysis of any text, document, code, or specification to find contradictions (e.g., code does X but spec says Y), ambiguities (vague terms, undefined criteria, multiple interpretations), inconsistencies (different names for the same concept), and logical gaps (missing steps in reasoning chains) — along with suggestions on how to fix each issue. ALWAYS use this skill when the user asks to review, critique, or analyze a document, codebase, spec, requirements, architecture decision, step-by-step explanation, or any text for quality issues. Use it for requests like "find problems with", "review critically", "check for contradictions", "verify consistency", "analyze for issues", "revisar documento", "analisar especificação", or "encontrar problemas em".

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).