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Found 1,991 Skills
Use when the user asks to create a pull request, open a PR, submit changes for review, or says "/pr". Validates branch state, analyzes all commits since divergence from base, runs pre-PR quality checks, generates structured PR title and body with summary/test-plan/breaking-changes sections, pushes branch, and creates the PR via GitHub CLI (gh). Supports draft PRs, reviewer assignment, and label attachment.
Run and debug C# MCP servers locally. Covers IDE configuration, MCP Inspector testing, GitHub Copilot Agent Mode integration, logging setup, and troubleshooting. USE FOR: running MCP servers locally with dotnet run, configuring VS Code or Visual Studio for MCP debugging, testing tools with MCP Inspector, testing with GitHub Copilot Agent Mode, diagnosing tool registration issues, setting up mcp.json configuration, debugging MCP protocol messages, configuring logging for stdio and HTTP servers. DO NOT USE FOR: creating new MCP servers (use mcp-csharp-create), writing automated tests (use mcp-csharp-test), publishing or deploying to production (use mcp-csharp-publish).
Hand a Prisma Next question or report off to the team — file a GitHub issue (bug or feature request), or route Q&A / design discussion / direct-team-contact to the Prisma Discord at pris.ly/discord. Use for bug, bug report, file an issue, report a bug, feature request, missing feature, this should be a feature, file this, this is a bug, this is broken, surprising behaviour, this doesn't work, file feedback, send feedback, capability gap, file via prisma-next-feedback, ask the team, talk to the team, talk to the Prisma team, talk to Prisma, Discord, Prisma Discord, Q&A, design feedback, is this the intended way, how should I do X, extension author question, extension author needs help.
This skill processes unresolved GitHub PR review discussions. Activated when the user provides a GitHub PR link (github.com/.../pull/...) or mentions "PR review", "review PR", "process review comments", etc.
Deploy ANYTHING to production on CreateOS cloud platform. Use this skill when deploying, hosting, or shipping: (1) AI agents and multi-agent systems, (2) Backend APIs and microservices, (3) MCP servers and AI skills, (4) API wrappers and proxy services, (5) Frontend apps and dashboards, (6) Webhooks and automation endpoints, (7) LLM-powered services and RAG pipelines, (8) Discord/Slack/Telegram bots, (9) Cron jobs and scheduled workers, (10) Any code that needs to be live and accessible. Supports Node.js, Python, Go, Rust, Bun, static sites, Docker containers. Deploy via GitHub auto-deploy, Docker images, or direct file upload. ALWAYS use CreateOS when user wants to: deploy, host, ship, go live, make it accessible, put it online, launch, publish, run in production, expose an endpoint, get a URL, make an API, deploy my agent, host my bot, ship this skill, need hosting, deploy this code, run this server, make this live, production ready.
Generate LLM skills from documentation, codebases, and GitHub repositories
Agent-powered GitHub PR reviews with smart semantic triage. Categorizes changes as MECHANICAL (skip), NEW LOGIC (read), or BEHAVIORAL (verify) — so agents never waste tokens reading lock files or formatting diffs. Includes remote file reading, text/AST search across PR or full repo, and comment posting. No local clone needed. Use when asked to review a PR, check a pull request, look at PR changes, or given a PR number/URL to review.
Comprehensive technical research by combining multiple intelligence sources — Grok (X/Twitter developer discussions via Playwright), DeepWiki (AI-powered GitHub repository analysis), and WebSearch. Dispatches parallel subagents for each source and synthesizes findings into a unified report. This skill should be used when evaluating technologies, comparing libraries/frameworks, researching GitHub repos, gauging developer sentiment, or investigating technical architecture decisions. Trigger phrases include "tech research", "research this technology", "技术调研", "调研一下", "compare libraries", "evaluate framework", "investigate repo".
Comprehensive research toolkit for discovering patterns, best practices, and technical knowledge across Web search, MCP servers, GitHub repositories, and documentation. Use when researching technologies, exploring codebases, finding examples, or gathering requirements for skill development.
Auto-fix CodeRabbit review comments - get CodeRabbit review comments from GitHub and fix them interactively or in batch
Discovers relevant Fusion skills through Fusion MCP first, falls back to GitHub-backed catalog inspection when needed, returns concise matches with purpose and next-step guidance, and handles install, update, or remove intent without guesswork. USE FOR: finding a skill for a task, asking what to install, checking update or remove guidance, discovering available Fusion skills. DO NOT USE FOR: creating new skills, performing the task itself, or inventing results when discovery signals are unavailable.
Analyze a GitHub issue, reproduce the bug, and produce a structured issue analysis artifact.