Explorar skills

Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.

Guide for creating beautiful Mermaid diagrams with proper styling for GitHub markdown (dark/light mode compatible, no icons).

Endpoint visibility, digital forensics, and incident response using Velociraptor Query Language (VQL) for evidence collection and threat hunting at scale. Use when: (1) Conducting forensic investigations across multiple endpoints, (2) Hunting for indicators of compromise or suspicious activities, (3) Collecting endpoint telemetry and artifacts for incident analysis, (4) Performing live response an

Generates and updates the latest app changelog based on git history since the last version tag.

Gera um esqueleto de repositório GitHub 'awesome-list' específico por tópico, completo com um README polido, regras de contribuição, instruções para agentes de IA, verificação de URL, licença e modelos reutilizáveis. Ideal para criar novos repositórios 'awesome', listas curadas ou catálogos de recursos por tópico a partir de um tópico e critérios opcionais.

End-to-end GitHub issue fix workflow using gh, local code changes, builds/tests, and git push. Use when asked to take an issue number, inspect the issue via gh, implement a fix, run XcodeBuildMCP builds/tests, commit with a closing message, and push.

Create commit messages following Sentry conventions. Use when committing code changes, writing commit messages, or formatting git history. Follows conventional commits with Sentry-specific issue references.

Inferencia reversa de especificações OpenSpec a partir do código, histórico do Git e documentos locais deste repositório, além de Jira/Confluence/URLs se disponíveis, sendo acionado por /inferspec-scan.

Browser automation skill for Lovable deployments. Activates when: - yolo_mode: on in CLAUDE.md - Running /deploy-edge or /apply-migration commands - After git push when auto_deploy: on (automatic detection) - Any mention of "yolo mode", "automate Lovable", "browser automation" Automatically navigates to Lovable.dev and submits deployment prompts. Runs verification tests based on configuration. Aut

Automate repetitive development tasks and workflows. Use when creating build scripts, automating deployments, or setting up development workflows. Handles npm scripts, Makefile, GitHub Actions workflows, and task automation.

Inspect GitHub PR checks with gh, pull failing GitHub Actions logs, summarize failure context, then create a fix plan and implement after user approval. Use when a user asks to debug or fix failing PR CI/CD checks on GitHub Actions and wants a plan + code changes; for external checks (e.g., Buildkite), only report the details URL and mark them out of scope.

Python statistical modeling: regression (OLS, WLS, GLM), discrete (Logit, Poisson, NegBin), time series (ARIMA, SARIMAX, VAR), with rigorous inference, diagnostics, and hypothesis tests. Use scikit-learn for ML; statistical-analysis for test choice.