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Saadhak (साधक) — the calibrated options agent

An autonomous, defined-risk options trading agent on Alpaca paper trading, built for the lablaFeatherless × Alpaca AI Trading Agents Hackathon.

The model proposes, the discipline decides, and a witness keeps score of how well the model knows what it knows. Saadhak states a probability with every thesis; a Brier score over those probabilities sets how much size the next trade is allowed. The agent has to earn the right to size up by knowing what it knows.

Three roles, each with a real technical boundary:

Role What it is Hard boundary
Niyama (the discipline) Deterministic risk engine + order builder The only code path that can create an order
Saadhak (the practitioner) A Featherless model connected as an MCP client to Alpaca's MCP server Its MCP server is started without the trading toolset, so it cannot place an order
Sakshi (the witness) Hash-chained journal, calibration scoring, reconciliation via the Alpaca CLI Never trades; can only halt

Every order is a defined-risk multi-leg options structure. There are no naked short options and no market orders. See PLAN.md for the full design.

Live dashboard: https://saadhak.streamlit.app

Slides: slides/index.html (reveal.js) · PDF: docs/slides.pdf · Video: docs/saadhak.mp4

Quickstart

cp .env.example .env     # add your Alpaca paper keys
uv sync
uv run saadhak status                 # account, clock, chain slice with deltas
uv run saadhak plan --symbol SPY      # build a condor and run the gates, no orders
uv run saadhak run --dry-run          # the full loop, orders printed not sent
ops/kill.sh                           # emergency stop

Book A (the deterministic theta book) needs no language model at all — it trades on greeks and the gates alone. The model only adds theses, catalyst trades, and calibration.

MIT licensed. Paper trading only.

About

An autonomous options agent on Alpaca that earns its position size by proving it knows what it knows. The model proposes, 19 deterministic gates decide, a witness keeps score.

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