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4,274 results
github/awesome-copilot
An agent user is a specialized user identity in Microsoft Entra ID that enables AI agents to act as digital workers. It allows agents to access APIs and services that strictly require user identities (e.g., Exchange mailboxes, Teams, org charts), while maintaining appropriate security boundaries.
wshobson/agents
Production-ready FastAPI project structures with async patterns, dependency injection, middleware, and best practices for building high-performance APIs.
Source provenance, compatibility, automated checks, and current evidence depth are available on the full page.
This workflow guides you through a systematic approach to identify missing features, prioritize them, and create detailed specifications for implementation.
Generate a complete, production-ready Model Context Protocol (MCP) server project in Go.
googleworkspace/cli
PREREQUISITE: Read ../gws-shared/SKILL.md for auth, global flags, and security rules. If missing, run gws generate-skills to create it.
Generate a complete, production-ready MCP server in Java using the official Java SDK with Maven or Gradle.
Generate a complete, production-ready Model Context Protocol (MCP) server project in Kotlin.
supercent-io/skills-template
Tracks LLM API costs, tokens, and latency using Tokuin CLI , and auto-generates a data-driven admin dashboard with PM insights.
mastra-ai/skills
Build AI applications with Mastra. This skill teaches you how to find current documentation and build agents and workflows.
This skill configures the Dataverse MCP server for GitHub Copilot with your organization's environment URL. Each organization is registered with a unique server name based on the org identifier (e.g., DataverseMcporgbc9a965c ). If the user provided a URL it is: $ARGUMENTS.
Generate a complete Power Platform custom connector with Model Context Protocol (MCP) integration for Microsoft Copilot Studio. This prompt creates all necessary files following Power Platform connector standards with MCP streamable HTTP support.
Analyze .agent.md or .prompt.md files to understand their purpose, complexity, and required capabilities, then recommend the most suitable AI model(s) from GitHub Copilot's available options. Provide rationale based on task characteristics, model strengths, cost-efficiency, and performance trade-offs.
Search the current repo (using #githubRepo for the repo info) and list any issues you find (using #list_issues) that are assigned to me.
magicseek/nblm
Query Google NotebookLM for source-grounded, citation-backed answers.
kepano/obsidian-skills
Base files use the .base extension and contain valid YAML.