BijectiveLabs / trading-research-agents

trading-research-agents 
 Autonomous trading agents with deterministic execution. The agents propose; the system decides. 
Language models are good at reading a market and saying what they think. They are bad at
arithmetic, they don't know what a trade costs, and they will happily overrule a limit you set.
This project uses them for the first part only. The system itself, fixed rules with no model
involved, fetches the data and works out every figure. The agents read those figures and give an
opinion. Then the system prices the trade, applies your limits, sizes it, and either writes it
down or sends one order with the stop attached. Every decision and every refusal is kept on disk
with its reason, so you can check afterwards what happened and why.
It's an early release, so expect settings to change between versions. What works
today: a universe of perpetuals found and measured by the system, a screener that picks where to
look, the full autonomous cycle on live data, four analysts and up to three validators, stops and
targets the analyst names inside bounds you set, the gates that decide, sizing from your own rules,
real orders on a venue's practice environment behind a mandate you sign, a risk manager that can
only make the desk more careful, and two auditors that read the records.
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## Contents
- What it solves
- Get started
- What you see, in order
- How one cycle decides
- Venues
- Models and providers
- Toward real orders
- Your money, your orders, your positions
- Watching a desk, and what is kept
- Command line
- What it guarantees, and what is not built yet
- Where it is going
- Documentation
## What it solves
| The usual problem with trading agents | What happens here |
|---|---|
| The model invents or miscalculates a number | Models never compute. Every figure comes from the system, and a figure a model cites is checked against its brief, value included. |
| Nobody knows what a trade cost until it's done | The round trip (fees, spread, impact, funding, slippage) is priced before an order exists, and a trade whose claimed edge doesn't clear it is refused. |
| The agent sizes its own position | Size comes from your conviction ladder and your risk limit. No model can make a trade bigger. |
| A model "decides" to ignore your settings | Your declared thresholds decide. A model's opinion is recorded beside them, never instead of them. |
| Something went wrong and there is no trace | Each cycle keeps its snapshot, briefs, answers, the intent and what the venue said. Nothing is rewritten. |
| A crash leaves a position with no stop | The stop and take profit go to the venue attached to the entry, so they survive this process dying. |
## Get started
A few minutes and one model key. Every setting has a working default, so a new desk runs before you
change anything; the table under step 6 says what those defaults are.
**1. Install.** You need Python 3.11 or newer. uv is the quickest way:
 [code] 
That brings every model provider and every exchang