Micro Agents
The smallest thing that acts: one signature, a few tools, a typed reply. Most agents in a production codebase should be this size.
from axllm import agent
assistant = agent("question:string -> answer:string", {"contextFields": []})
out = assistant.forward(client, {"question": "Capital of France?"})That is the whole program. There is no prompt to write, no parser to maintain, no retry loop to hand-roll — the signature generates all three, and the reply comes back as typed data.
Zero Config Is The Full Harness
A micro agent is not a lesser mode. With no configuration, agent() already runs the complete pipeline — distiller, executor with a live runtime session, responder — the same machinery the long-horizon tier uses. You just haven’t needed to touch any of it yet. Two practical consequences:
- Typed outputs are the system boundary. The reply is validated against the signature and retried with feedback on mismatch, so downstream code consumes data, not prose.
- Actions really run. Tools execute in the runtime; results are inspected before the agent answers. A micro agent that looks up an order answers from the record it fetched, not from a guess.
Keeping It Micro
- One signature, one job. If the task description needs the word “then”, consider two agents or a flow.
- Pass tools flat —
functions: [lookupOrder, sendReply]. At this size every callable is obviously relevant, and flat inline tools are the most reliable shape for small models (grouped discovery earns its keep later, at catalog scale). - Small models are the point. Micro agents run well on cheap, fast models — see Performance for measured model guidance.
When To Graduate
Move up a tier when one of these appears:
| Signal | Go to |
|---|---|
| The tool list is growing past what fits comfortably in one prompt | Standard — namespaces, groups, discovery |
| A specialist should own part of the job (its own signature, tools, identity) | Standard — child agents |
| An input field is getting bulky (logs, ledgers, transcripts) | Long-horizon — context fields |
| Runs are getting long, or the same material is queried repeatedly | Long-horizon — policies, maps, memory |
Runnable code: agent examples and the agent() API.