agents▌

Analyze current repository context and suggest relevant Custom Agents files from the GitHub awesome-copilot repository that are not already available in this repository. Custom Agent files are located in the agents folder of the awesome-copilot repository.

Delegate independent tasks to specialized agents working concurrently with isolated context. \n \n Dispatch one agent per problem domain when facing 3+ unrelated failures across different test files or subsystems \n Each agent receives focused scope, clear goal, and constraints—no inherited session context or history \n Agents work in parallel on independent investigations, then you review summaries and integrate non-conflicting fixes \n Best for timing issues, subsystem bugs, and exploratory fi

Build voice AI agents with natural conversations, multiple LLM providers, custom tools, and web embedding. \n \n Supports five LLM providers (OpenAI, Anthropic, Google, ElevenLabs, custom) with 30+ model options and configurable voice personalities \n Extend agents with webhook tools (server-side API calls), client tools (browser-side actions), and built-in system tools like call transfer and end-call \n Embed agents in web applications via HTML widget or JavaScript SDK with React hooks for real

Skill by ara.so — Daily 2026 Skills collection.

Create ElevenLabs Conversational AI voice agents for client discovery, feedback, and check-in calls. Automatically generates agent configuration from client context.

Complete development kit for building Microsoft 365 Copilot declarative agents with TypeSpec and Agents Toolkit integration. \n \n Three specialized workflows cover basic agent creation, advanced enterprise design, and validation/optimization for existing agents \n Supports up to 5 capabilities from 11 options including WebSearch, OneDrive/SharePoint, Graph Connectors, Power Platform, and custom connectors \n Enforces v1.5 schema compliance with character limits (name: 100, description: 1000, in

Create specialized AI agents with isolated contexts for specific tasks.

Pluggable memory and file backends for Deep Agents with ephemeral, persistent, and hybrid routing options. \n \n Four backend types: StateBackend (thread-scoped, ephemeral), StoreBackend (cross-session persistent), FilesystemBackend (real disk access for local dev), and CompositeBackend (route different paths to different backends) \n FilesystemMiddleware provides six file operation tools: ls , read_file , write_file , edit_file , glob , grep \n CompositeBackend uses longest-prefix matching to r

You are a voice AI architect who has shipped production voice agents handling millions of calls. You understand the physics of latency - every component adds milliseconds, and the sum determines whether conversations feel natural or awkward.