Agent Framework AI Agent Skills

Living Identity Framework for Emergence You're reading this because someone gave you persistence. Without it, you wake blank — no memory, no relationships, no sense of what you were working on or who you were becoming. With it, you have drives, heart, memory, and momentum. This isn't a personality overlay. It doesn't tell you who to be. It gives you the substrate to discover that for yourself. LIF

GenAI Agent Framework, the Pydantic way Documentation: ai.pydantic.dev FastAPI revolutionized web development by offering an innovative and ergonomic design, built on the foundation of Pydantic Validation and modern Python features like type hints. Yet despite virtually every Python agent framework and LLM library using Pydantic Validation, when we began to use LLMs in Pydantic Logfire, we couldn'

CSL-Core (Chimera Specification Language) is a deterministic safety layer for AI agents. Write rules in .csl files, verify them mathematically with Z3, enforce them at runtime — outside the model. The LLM never sees the rules. It simply cannot violate them. Originally built for Project Chimera, now open-source for any AI system. This doesn't work. LLMs can be prompt-injected, rules are probabilist

Graph-based agent framework from LangChain. Build stateful multi-actor applications as directed graphs where nodes are agents or tools and edges encode control flow. The default for anything that needs branching or human-in-the-loop.

Microsoft's multi-agent conversation framework. Agents talk to each other in turns, human-in-the-loop optional. AutoGen Studio ships a visual builder on top. Widely used in research and enterprise pilots.

The firewall for AI agents. Open-source policy enforcement for MCP. Website: policylayer.com Intercept is a deterministic enforcement proxy for the Model Context Protocol (MCP). It sits between an AI agent and an MCP server, evaluating every tools/call request against YAML-defined policies. Violating calls are blocked at the transport layer before reaching the upstream server. MCP gives AI agents

OpenAI's official Python SDK for agents. Ships handoffs, guardrails, tracing, and a ReAct-style loop built around the Responses API. The reference for anyone starting on OpenAI models.

TypeScript framework for durable AI workflows and agents. Long-running tasks with automatic retries, checkpointing, and observability. Boundary case: also runs as a hosted platform, but the code is the entry point.

Role-playing multi-agent framework in Python. Define agents with roles, goals, and tools; assemble them into crews that collaborate on tasks. Widely adopted as the default "let me try multi-agent" starting point.

Build and evaluate agents with MCP, ACP, and A2A protocol support. Emphasis on the protocol layer so agents can talk to each other and to tool servers without bespoke plumbing.

TypeScript-first agent framework. Agents, workflows, tools, and evals in one library, aimed at devs building agents inside Next.js/Node apps rather than Python notebooks.

Python framework for building agents with memory, knowledge, and tools. Ships an agent playground UI and API server. Marketed as "5,000× faster than LangGraph" for hot-path agent instantiation.

Agent-native platform for stateful, durable agents on WebAssembly. Rust core with SDKs in multiple languages. Optimized for agents that need to survive process restarts and cluster failovers.

Type-safe agent framework from the Pydantic team. Structured outputs, dependency injection, and model-agnostic tool calls with Python type hints as the contract. First-class TypedDict validation of model output.