agentic-loopslisted

# Agentic Loops: Agents, Tools, Workflows Structured patterns for building multi-turn agents that reason, act, and observe. An **agentic loop** is: 1. **Think**: Agent reasons about task → decides action 2. **Act**: Call tools / take action 3. **Observe**: Get result, update state 4. **Repeat**: Loop until task complete --- ## Minimal Loop — use the tested implementation, don't hand-roll this Don't write a bespoke think/act/observe loop from scratch — it's easy to get the tool-result protocol wrong (feeding a tool's result back as a plain `"user"` message loses the call binding and looks like human input to the model, instead of `{"role": "tool", "tool_call_id": ..., ...}`), easy to leave out a budget (infinite loop if the model never stops calling tools), and easy to skip argument validation (a malformed tool call reaches your tool function instead of being rejected). `agent_loop.py`, bundled alongside this file (a symlink back to `patterns/agentic-loops/agent_loop.py`, so it resolves whether you installed the whole harness or only this one skill), is a minimal, tested (100% coverage), provider-neutral implementation that gets these right: JSON-Schema-validated arguments, provider-correct tool-result messages, an iteration + wall-clock budget, an optional approval hook, and an auditable trace that never logs raw tool output. See `patterns/agentic-loops/README.md` in the full harness checkout for the complete usage example and what it does *not* cover (sandboxing, promp