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AI FLUENCY — CHEAT SHEET
Agents & Tool Use
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Agentic loops, function calling, MCP, evals, multi-agent patterns.
6 terms

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* Agent
  A system where an LLM autonomously plans, calls tools, observes results, and iterates toward a goal rather than producing one-shot output.
  e.g. An agent that books a flight by searching, comparing, and confirming.

* Agentic Loop
  The repeating cycle of think → act → observe that lets an agent make progress on a task across multiple steps.
  e.g. Search, read the result, decide the next search, repeat.

* Eval (Evaluation)
  A structured test suite used to measure how well a model or agent performs a task, often used to catch regressions before shipping changes.
  e.g. Running 200 saved tasks against a new prompt to check the pass rate.

* Function Calling / Tool Use
  A model's ability to emit a structured request to invoke an external function or API, then incorporate the result into its response.
  e.g. Calling a get_weather(city) function instead of guessing.

* Model Context Protocol (MCP)
  An open standard for connecting AI models to external tools, data sources, and systems through a common interface.
  e.g. One MCP server exposing both a database and a filesystem to any compatible client.

* Multi-Agent System
  Multiple specialized agents (or agent instances) coordinating, delegating, or debating to solve a task none could solve as well alone.
  e.g. A "planner" agent delegating research to a "researcher" agent.

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Tip: paste this file into your favorite AI assistant and ask to be tutored on it.