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Found 101 Skills
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.
Server-Sent Events (SSE) streaming for Claude API with support for text, tool use, and extended thinking. Activate for real-time responses, stream handling, and progressive output.
Use when you want to expose an n8n workflow as a tool the coding agent can call. Two cases. (1) Wrap n8n API capabilities the MCP doesn't natively expose: folder CRUD, tag rename/delete, instance metadata, credential creation. (2) Expose a general-purpose workflow as an agent tool: a workflow that calls a third-party API, runs business logic, or does any task you want the agent to invoke. Triggers on "expose as MCP tool", "build a tool for my agent", "I need to know X" where X isn't an MCP tool, "create folder", "rename tag", or any capability gap.
Build reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, reuse, shared/common logic, modular workflows, "Define Below" inputs, waitForSubWorkflow, mode each vs all, or exposing a workflow as an agent tool. Covers typed sub-workflow inputs, all-vs-each execution, verb-first naming for discovery, stateless vs stateful design, and splitting by input shape.
When you want to integrate an external tool, API, MCP server, or service into a project — the wizard walks you through auth, config, env vars, client wrapper code, example usage, and (optionally) a smoke-test. Scoped to Next.js and Rails projects (the two primary stacks). Interactive Q&A pattern — starts with the tool name, asks structured questions until the integration is fully specified, then scaffolds files. Examples of tools to toolify — Stripe, Kit, Sanity, Notion, Neon, Supabase, Fathom, Rewardful, SavvyCal, Riverside, ScrapeCreators, Anthropic, OpenAI, Gemini, Twilio, Resend, Postmark, Vercel Blob, custom internal APIs. For MCP servers specifically, also handles the .mcp.json wiring. Triggers on "/toolify," "integrate X," "add X to this project," "wire up X," "set up the X integration," "hook up X," "connect X," "add MCP for X." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code. NOT for adding new SKILL.md files — that's skillify. NOT for cron/agent loops — that's loopify.
Guide for creating effective skills. Use when users want to create a new skill that extends the assistant's capabilities with specialized knowledge, workflows, or tool integrations.
Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.
A guide to creating efficient Skills. Use this skill when users need to create a new skill (or update an existing one) to extend Claude's capabilities through expertise, workflows, or tool integrations.
Work decomposition, dependency ordering, and status tracking for software tasks. Activate when breaking down features into tasks, managing work items, tracking dependencies, creating stories or epics, or asking what to work on next. Works with any task tool: harness-native todos, dot CLI, GitHub Issues, or file-based tracking.
Comprehensive knowledge of Microsoft Agent Framework for building production AI agents and workflows. Auto-activates for agent building, workflow design, AutoGen migration, and enterprise AI tasks.
Deep-dive analysis of GitHub projects. Use when the user mentions a GitHub repo/project name and wants to understand it — triggered by phrases like "help me look at this project", "learn about XXX", "how is this project", "analyze the repo", or any request to explore/evaluate a GitHub project. Covers architecture, community health, competitive landscape, and cross-platform knowledge sources.
Analyze Trigger.dev tasks, schedules, and runs for cost optimization opportunities. Use when asked to reduce spend, optimize costs, audit usage, right-size machines, or review task efficiency. Requires Trigger.dev MCP tools for run analysis.