Automate Close CRM tasks via Rube MCP (Composio): create leads, manage calls/SMS, handle tasks, and track notes. Always search tools first for current schemas.

Automate Discord tasks via Rube MCP (Composio): messages, channels, roles, webhooks, reactions. Always search tools first for current schemas.

Automate HelpDesk tasks via Rube MCP (Composio): list tickets, manage views, use canned responses, and configure custom fields. Always search tools first for current schemas.

Automate Jira tasks via Rube MCP (Composio): issues, projects, sprints, boards, comments, users. Always search tools first for current schemas.

Discover, list, create, edit, toggle, copy, move, and delete AI agent skills across 11 tools (Cursor, Claude, Agents, Windsurf, Copilot, Codex, Cline, Aider, Continue, Roo Code, Augment)

Cheatsheet for the Mercury (proton) MCP tools. Use when connected to the Mercury MCP server to look up which mercury_* tool to call for messaging teammates, threads, tasks, automations, or admin team-graph edits.

Automate Salesforce tasks via Rube MCP (Composio): leads, contacts, accounts, opportunities, SOQL queries. Always search tools first for current schemas.

Automate Square tasks via Rube MCP (Composio): payments, orders, invoices, locations. Always search tools first for current schemas.

This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.

Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.

Use when working with error debugging multi agent review

Assess worker-classification and compliance risk for temporary event staffing in the US and Canada — W-2 vs 1099, misclassification penalties, joint-employer liability, COI, and wage/hour rules. Includes live state-by-state lookups via MCP.

Job search automation, auto apply, resume generation, application tracking, salary intelligence, and recruiter outreach using the JobGPT MCP server.

Automate Linear tasks via Rube MCP (Composio): issues, projects, cycles, teams, labels. Always search tools first for current schemas.

Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage.

Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.

Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.

Use when working with performance testing review multi agent review

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.

Automate Shopify tasks via Rube MCP (Composio): products, orders, customers, inventory, collections. Always search tools first for current schemas.

Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.

Lightweight Gmail integration with standalone OAuth authentication. No MCP server required.

Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.

Lightweight Google Calendar integration with standalone OAuth authentication. No MCP server required.

Lightweight Google Drive integration with standalone OAuth authentication. No MCP server required. Full read/write access.

Lightweight Google Sheets integration with standalone OAuth authentication. No MCP server required. Full read/write access.

Lightweight Google Slides integration with standalone OAuth authentication. No MCP server required. Full read/write access.

Debug the current iOS project on a booted simulator with XcodeBuildMCP.

Scan prompt history for recurring patterns and unmet needs, then propose new skills or command templates

To provide a comprehensive reference for configuring and using Claude Code (the agentic coding tool) to its full potential. This skill synthesizes best practices, configuration templates, and advanced usage patterns.

Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similar

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Lightweight Google Docs integration with standalone OAuth authentication. No MCP server required.

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).

Vector-powered CLI for semantic file search with a Claude/Codex skill

Use when creating, editing, or generating draw.io diagram files (.drawio, .drawio.svg, .drawio.png). Covers mxGraph XML authoring, shape libraries, style strings, flowcharts, system architecture, sequence diagrams, ER diagrams, UML class diagrams, network topology, layout strategy, the hediet.vscode-drawio VS Code extension, and the full agent workflow from request to a ready-to-open file.

A persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch.

Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.

Build and run evaluators for AI/LLM applications using Phoenix.

Create, update, and manage GitHub issues using MCP tools. Use this skill when users want to create bug reports, feature requests, or task issues, update existing issues, add labels/assignees/milestones, set issue fields (dates, priority, custom fields), set issue types, manage issue workflows, link issues, add dependencies, or track blocked-by/blocking relationships. Triggers on requests like "create an issue", "file a bug", "request a feature", "update issue X", "set the priority", "set the start date", "link issues", "add dependency", "blocked by", "blocking", or any GitHub issue management task.

Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.

Comprehensive guide for configuring and managing GitHub Dependabot. Use this skill when users ask about creating or optimizing dependabot.yml files, managing Dependabot pull requests, configuring dependency update strategies, setting up grouped updates, monorepo patterns, multi-ecosystem groups, security update configuration, auto-triage rules, or any GitHub Advanced Security (GHAS) supply chain security topic related to Dependabot. For pre-commit dependency vulnerability scanning in AI coding agents via the GitHub MCP Server, this skill references the Advanced Security plugin (`advanced-security@copilot-plugins`). Use this skill when an agent needs to scan dependencies for known vulnerabilities before committing.

Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.

Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.

Interactive training for the GitHub Copilot CLI. Guided lessons, quizzes, scenario challenges, and a full reference covering slash commands, shortcuts, modes, agents, skills, MCP, and configuration. Say "cliexpert" to start.

Guide for configuring and managing GitHub secret scanning, push protection, custom patterns, and secret alert remediation. For pre-commit secret scanning in AI coding agents via the GitHub MCP Server, this skill references the Advanced Security plugin (`advanced-security@copilot-plugins`). Use this skill when enabling secret scanning, setting up push protection, defining custom patterns, triaging alerts, resolving blocked pushes, or when an agent needs to scan code for secrets before committing.

Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.

Plain-English translation layer for non-technical Copilot CLI users. Translates every approval prompt, error message, and technical output into clear, jargon-free English with color-coded risk indicators.

Bootstrap and run a multi-agent AI development team. Use when: starting a new software project with AI agents, setting up parallel dev/QA teams, creating sprint plans, writing brainstorm prompts with distinct agent voices, recovering a project workflow, or planning sprints.

Go-to-market strategy for AI products. Use when positioning AI products, handling "who is responsible when it breaks" objections, pricing variable-cost AI, choosing between copilot/agent/teammate framing, or selling autonomous tools into enterprises.

Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)

Govern Power Automate flows and Power Apps at scale using the FlowStudio MCP cached store. Classify flows by business impact, detect orphaned resources, audit connector usage, enforce compliance standards, manage notification rules, and compute governance scores — all without Dataverse or the CoE Starter Kit. Load this skill when asked to: tag or classify flows, set business impact, assign ownership, detect orphans, audit connectors, check compliance, compute archive scores, manage notification rules, run a governance review, generate a compliance report, offboard a maker, or any task that involves writing governance metadata to flows. Requires a FlowStudio for Teams or MCP Pro+ subscription — see https://mcp.flowstudio.app

Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"

Pro+ subscription required. Tenant-wide Power Automate monitoring using the FlowStudio MCP cached store: failure rates, run-health trends, maker/app inventory, inactive owners, and compliance/health reports. Use only for aggregated tenant views. For one environment, one flow, run control, or root-cause debugging, use flowstudio-power-automate-mcp, flowstudio-power-automate-debug, or the server monitor-flow bundle. Requires FlowStudio for Teams or MCP Pro+.

Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"

Audit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP servers use pinned versions (not @latest) - Detecting unpinned dependencies in MCP server configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]

Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

Issue Planning and Automation prompt that generates comprehensive project plans with Epic > Feature > Story/Enabler > Test hierarchy, dependencies, priorities, and automated tracking.

Test Planning and Quality Assurance prompt that generates comprehensive test strategies, task breakdowns, and quality validation plans for GitHub projects.

Write a coding standards document for a project using the coding styles from the file(s) and/or folder(s) passed as arguments in the prompt.

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.

Create tldr summaries for GitHub Copilot files (prompts, agents, instructions, collections), MCP servers, or documentation from URLs and queries.

Convert a text-based document to markdown following instructions from prompt, or if a documented option is passed, follow the instructions for that option.

Skill converted from mcp-create-adaptive-cards.prompt.md

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

Expert-level browser automation, debugging, and performance analysis using Chrome DevTools MCP. Use for interacting with web pages, capturing screenshots, analyzing network traffic, and profiling performance.

Systematic Power BI performance troubleshooting prompt for identifying, diagnosing, and resolving performance issues in Power BI models, reports, and queries.

Prompt for generating an AGENTS.md file for a repository

Skill converted from mcp-create-declarative-agent.prompt.md

Intelligent README.md generation prompt that analyzes project documentation structure and creates comprehensive repository documentation. Scans .github/copilot directory files and copilot-instructions.md to extract project information, technology stack, architecture, development workflow, coding standards, and testing approaches while generating well-structured markdown documentation with proper formatting, cross-references, and developer-focused content.

Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.

Generate complete Power Platform custom connector with MCP integration for Copilot Studio - includes schema generation, troubleshooting, and validation

Guides the Copilot CLI on how to use the WorkIQ CLI/MCP server to query Microsoft 365 Copilot data (emails, meetings, docs, Teams, people) for live context, summaries, and recommendations.

Perform a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.

Comprehensive Power BI DAX formula optimization prompt for improving performance, readability, and maintainability of DAX calculations.

Prompt for creating detailed feature implementation plans, following Epoch monorepo structure.

Prompt and workflow for generating conventional commit messages using a structured XML format. Guides users to create standardized, descriptive commit messages in line with the Conventional Commits specification, including instructions, examples, and validation.

Generate a complete MCP server implementation optimized for Copilot Studio integration with proper schema constraints and streamable HTTP support

Prompt for creating an Epic Product Requirements Document (PRD) for a new epic. This PRD will be used as input for generating a technical architecture specification.

Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers, list available MCP servers/tools, or call MCP tools from command line.

Generate a complete MCP server project in Python with tools, resources, and proper configuration

A micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.

Structured Autonomy Implementation Generator Prompt

Generate a complete MCP server project in TypeScript with tools, resources, and proper configuration

Generate a complete TypeSpec declarative agent with instructions, capabilities, and conversation starters for Microsoft 365 Copilot

Interactive prompt refinement workflow: interrogates scope, deliverables, constraints; copies final markdown to clipboard; never writes code. Requires the Joyride extension.

Prompt for creating the high-level technical architecture for an Epic, based on a Product Requirements Document.

Prompt for creating Product Requirements Documents (PRDs) for new features, based on an Epic.

Structured Autonomy Planning Prompt

Finalize prompt file using the role of an AI agent to polish the prompt for the end user.

Website exploration for testing using Playwright MCP