Explorar skills

Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts

Analyze and resolve Sentry comments on GitHub Pull Requests. Use this when asked to review or fix issues identified by Sentry in PR comments. Can review specific PRs by number or automatically find recent PRs with Sentry feedback.

Ajuda iniciantes e não programadores a fazerem uma codificação mais segura, transformando uma ideia de software bruta em um plano de projeto pequeno, claro e legível por IA antes da implementação. Também orienta a inicialização segura do projeto, configuração do Python uv, checkpoints git, pull requests, merges, atualizações de documentos, testes e manutenção de wiki legível por IA.

Use when receiving UAT feedback, bug reports, user testing results, stakeholder feedback, QA findings, or any batch of issues to investigate. Investigates each item BEFORE creating issues, classifies by type and priority, creates well-formed GitHub issues with proper project board integration.

Use when reviewing git state across worktrees, stashes, and branches - helps decide what to clean up, resume, or address

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

Use when writing code in typed languages - enforces full typing with no any/unknown/untyped escapes, even if it requires extra time

Use for LARGE work requiring feature-level grouping. Creates epic tracking issues, manages related issues under a common label, tracks epic progress, and coordinates with milestones.

Use after code review - implement ALL findings; any finding not fixed MUST have tracking issue created; no finding disappears without trace

Deep-validate a single GitHub issue against the codebase: cross-reference file paths, detect already-implemented features, check for related PRs, verify dependencies, and deliver a structured verdict with recommended action. Triggers: review issue, validate issue, check issue status, is this issue still needed, issue review.

Use to spawn isolated worker processes for autonomous issue work. Uses Task tool with run_in_background for parallel execution and TaskOutput for monitoring. Pre-extracts context to minimize worker token usage.

Setup Sentry AI Agent Monitoring in any project. Use this when asked to add AI monitoring, track LLM calls, monitor AI agents, or instrument OpenAI/Anthropic/Vercel AI/LangChain/Google GenAI. Automatically detects installed AI SDKs and configures the appropriate Sentry integration.