Selection Agents
The Selection team picks the top-N tickers for a
(model, strategy, universe, agent) quadruple. It is the bridge
between the Research team's universe candidates and the Trader team's
signal-emitter loop.
Spec
selection.stock_selector — implemented in
alphaswarm/agents/selection/stock_selector.py.
RAG
| Layer | Used for |
|---|---|
L0 (decisions) | Past agent_decisions outcomes — paper RAG#0. |
L1 (performance) | Recent backtest performance windows. |
L2 (financial_ratios, sec_xbrl) | Discriminate between similar candidates. |
Tool: regulatory_lookup | Tail-risk veto. |
Memory + annotations
Every pick is persisted via annotation with label="pick" and a
payload {score, rationale, evidence, vetoed_by?} so the optimisation
analysis layer can inspect the historical edge of each combo.
REST
POST /agents/selection/run — async via Celery
POST /agents/selection/sync — synchronous variant
GET /agents/selection/runs — recent runs
GET /agents/selection/annotations — pick rationale history