
CrewAI
Framework for orchestrating role-playing, autonomous agents that collaborate on tasks.
Website captured Oct 19
Split work across agents with clean, isolated contexts: agent frameworks, sub-agents, handoffs, workflows.
17 listed entries

Framework for orchestrating role-playing, autonomous agents that collaborate on tasks.
Website captured Oct 19

Framework for stateful, long-running agents built as graphs, with checkpoints and human-in-the-loop.
Website captured Oct 19

Framework and runtime for building, running and managing multi-agent systems.
Website captured Oct 19

Framework for programming, not prompting, language models: modules and optimizers that compile prompts.
Website captured Oct 19

Lightweight framework for multi-agent workflows with handoffs, guardrails and tracing.
Website captured Oct 19

Hugging Face's barebones library for agents that think and act in code.
Website captured Oct 19

TypeScript framework for AI agents, workflows, RAG and memory.
Website captured Oct 19

TypeScript toolkit for AI apps and agents: tool calling, streaming and structured output across providers.
Website captured Oct 19

Google's code-first toolkit for building, evaluating and deploying agents (Python, with a JS SDK).
Website captured Oct 19

Type-safe Python agent framework from the Pydantic team, working across model providers.
Website captured Oct 19

Microsoft's framework (Python and .NET) for building, orchestrating and deploying agents and multi-agent workflows.
Website captured Oct 19

A programming language for agents: typed prompt functions with schema-aligned parsing of model output.
Website captured Oct 19

Build agents on Claude Code's harness from code: tools, sub-agents, context management and permissions.
Website captured Oct 19
The set of strategies for curating and maintaining the optimal set of tokens during LLM inference, including everything that lands in context outside the prompt.
Leave failed actions and error messages in the history so the model learns from them instead of repeating them.
Give focused tasks to sub-agents with clean context windows; they return condensed summaries to a lead agent.
LangChain's four buckets of context engineering: save context outside the window, pull the right parts in, shrink it, or split it across agents and environments.