Outlook calendar automation
Automate Outlook Calendar tasks via Rube MCP (Composio): create events, manage attendees, find meeting times, and handle invitations. Always search tools first for current schemas.
Skills for your AI
Automate Outlook Calendar tasks via Rube MCP (Composio): create events, manage attendees, find meeting times, and handle invitations. Always search tools first for current schemas.
Automate PagerDuty tasks via Rube MCP (Composio): manage incidents, services, schedules, escalation policies, and on-call rotations. Always search tools first for current schemas.
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Search the public web and verify sources with Parallel's free Search MCP. Use when the user chooses Parallel or its connected tools for current information and URL extraction.
Delegate coding tasks to the Pi coding agent CLI (`pi`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
Give an AI agent a permanent network address, encrypted P2P messaging, and an installable app store via Pilot Protocol
Build a low-latency, Iron Man-inspired tactical voice assistant (F.R.I.D.A.Y.) using Pipecat, Gemini, and OpenAI.
Coordinate multi-vendor AI agents as a self-improving team — a learning router assigns work by track record and citizens can amend the protocol's own rules.
Polis Protocol: A Self-Optimizing City of Agents
Automate PostHog tasks via Rube MCP (Composio): events, feature flags, projects, user profiles, annotations. Always search tools first for current schemas.
Automate Postmark email delivery tasks via Rube MCP (Composio): send templated emails, manage templates, monitor delivery stats and bounces. Always search tools first for current schemas.
Optimize pull requests for quick approval and merging by ensuring clean diffs, comprehensive self-reviews, and structured documentation.
Create pull requests following Sentry's engineering practices.
This skill covers the principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development.
Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation)
Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
Agent governance skill for MCP tool calls — Cedar policy authoring, shadow-to-enforce rollout, and Ed25519 receipt verification.
Generates Puppeteer scripts for browser automation, scraping, and PDF generation. Triggers on: "Puppeteer", "headless Chrome", "page.goto", "scrape", "PDF generation".
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
Delegate coding tasks to the Qoder CLI (`qodercli`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.
RAG (Retrieval-Augmented Generation) implementation workflow covering embedding selection, vector database setup, chunking strategies, and retrieval optimization.