Agents & Tool Use
Function calling, ReAct loops, MCP, agent memory architectures and evaluation harnesses.
15concepts
169flashcards
117minutes of reading
- 01 Agent Frameworks Compared LangGraph, CrewAI, AutoGen, and the OpenAI Agents SDK solve different problems; the harder question is whether you need a framework at all.
- 02 Agent Skills and Progressive Disclosure Packaging agent expertise as folders of instructions and scripts that load in layers, so a hundred specialisations cost a few hundred tokens until one of them is actually needed.
- 03 Agent-to-Agent Interoperability MCP standardises how one agent reaches tools and data; A2A standardises how two independently built agents discover each other and collaborate as peers, which is a different problem with a different failure surface.
- 04 Model Context Protocol (MCP) The open standard that replaces bespoke per-tool integrations with one protocol, so any compliant client can talk to any compliant server.
- 05 Planning and Task Decomposition in Agents Why an LLM that reasons well step by step still fails to produce a valid multi-step plan, and how decomposition, external planners, and replanning close the gap.
- 06 Tool Use and Function Calling How models invoke external tools to fetch data, run code, and take actions in the world.