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README.md

@@ -65,12 +65,21 @@ per-tier abstention and latency are in
 
 ## Serving
 
-`assay.server` exposes `POST /v1/decide`, the System One style `POST /v1/systemone`
-(questions typed `choice`/`noul`/`score` with options under `criteria`, plus a batch
-endpoint), and `POST /v1/decide_graph`, which walks a decision tree in a single forward pass.
-Requests arriving together are answered in one pass; `/health` and `/metrics` are for
+```bash
+python -m assay.server --model Berk/assay-compiled-base --port 8000
+```
+
+`POST /v1/decide` is the native shape; `POST /v1/systemone` and `/v1/systemone/batch` accept
+the shape other open decision models use (`criteria` options, `noul` booleans); `POST
+/v1/decide_graph` walks a decision tree in one forward pass; `POST /v1/agents` registers an
+agent -- a graph plus the actions its outcomes stand for -- and `/v1/agents/<name>/run`
+decides a case. Requests arriving together share a pass, and `/health` and `/metrics` are for
 operations. `assay.backends.sglang` runs the same model on an SGLang deployment.
 
+Guides: [deployment and the full API](https://github.com/bgokden/assay/blob/main/docs/serving.md),
+[agents](https://github.com/bgokden/assay/blob/main/docs/agents.md),
+[runnable examples](https://github.com/bgokden/assay/tree/main/examples).
+
 ## Train one on your own data
 
 `python -m assay.pipeline --config <your>.json` runs training, temperature calibration,