trading-research-agents

<p align="center"> <a href="https://www.bijectivelabs.dev"><img src="assets/bijective_banner.png" alt="Bijective Labs"></a> </p> <h1 align="center">trading-research-agents</h1> <p align="center"><strong>Autonomous trading agents with deterministic execution. The agents propose; the system decides.</strong></p> <!-- mcp-name: io.github.BijectiveLabs/trading-research-agents --> <p align="center"> <a href="https://github.com/BijectiveLabs/trading-research-agents/actions/workflows/ci.yml"><img alt="CI" src="https://github.com/BijectiveLabs/trading-research-agents/actions/workflows/ci.yml/badge.svg?branch=master"></a> <a href="https://pypi.org/project/trading-research-agents/"><img alt="PyPI" src="https://img.shields.io/pypi/v/trading-research-agents?style=flat-square&logo=pypi&logoColor=white&label=PyPI&cacheSeconds=1800"></a> <a href="https://pypi.org/project/trading-research-agents/"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/trading-research-agents?style=flat-square&logo=python&logoColor=white&label=python&cacheSeconds=1800"></a> <a href="https://github.com/BijectiveLabs/trading-research-agents/blob/master/LICENSE"><img alt="License: MIT" src="https://img.shields.io/badge/license-MIT-blue?style=flat-square"></a> <img alt="Status: alpha" src="https://img.shields.io/badge/status-alpha-orange?style=flat-square"> </p> <p align="center"> <img alt="Managed with uv" src="https://img.shields.io/badge/uv-managed-DE5FE9?style=flat-square&logo=uv&logoColor=white"> <img alt="Linted and formatted with Ruff" src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json&style=flat-square"> <img alt="Type checked with mypy" src="https://img.shields.io/badge/types-mypy-2A6DB2?style=flat-square"> <img alt="Venues through ccxt" src="https://img.shields.io/badge/venues-ccxt-0F766E?style=flat-square"> <img alt="Tested on Linux and Windows" src="https://img.shields.io/badge/tested%20on-Linux%20%7C%20Windows-0969DA?style=flat-square"> </p> <p align="center"> <a href="https://www.bijectivelabs.dev/open-source"><img alt="Website" src="https://img.shields.io/badge/web-bijectivelabs.dev%2Fopen--source-1d2a3d?style=flat-square"></a> <a href="https://docs.bijectivelabs.dev"><img alt="Documentation" src="https://img.shields.io/badge/docs-docs.bijectivelabs.dev-1f6feb?style=flat-square"></a> <a href="https://www.bijectivelabs.dev/insights"><img alt="Insights" src="https://img.shields.io/badge/insights-bijectivelabs.dev%2Finsights-6f42c1?style=flat-square"></a> <a href="https://github.com/BijectiveLabs/trading-research-agents/blob/master/CHANGELOG.md"><img alt="Changelog" src="https://img.shields.io/badge/changelog-CHANGELOG.md-E05735?style=flat-square"></a> <a href="https://github.com/BijectiveLabs/trading-research-agents/blob/master/SECURITY.md"><img alt="Security policy" src="https://img.shields.io/badge/security-policy-2ea44f?style=flat-square"></a> </p> <br> 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: linear perpetuals, spot pairs (stock perpetuals and tokenized stocks among them) and prediction market outcomes through one order path, 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. --- ## Contents - [What it solves](#what-it-solves) - [Get started](#get-started) - [What you see, in order](#what-you-see-in-order) - [How one cycle decides](#how-one-cycle-decides) - [Venues](#venues) - [Models and providers](#models-and-providers) - [Toward real orders](#toward-real-orders) - [Your money, your orders, your positions](#your-money-your-orders-your-positions) - [Watching a desk, and what is kept](#watching-a-desk-and-what-is-kept) - [Command line](#command-line) - [What it guarantees, and what is not built yet](#what-it-guarantees-and-what-is-not-built-yet) - [Where it is going](#where-it-is-going) - [Documentation](#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 with the entry, or right after the fill where the venue takes them no other way, so they survive this process dying. | | Text from a feed tells the model what to do | The model that proposes a direction reads numbers code computed; outside text reaches only roles that decide nothing, and no model can send an order or reach a key. | None of these is hypothetical. [Why it is built this way](https://docs.bijectivelabs.dev/opensource/why) lists the documented failures behind each one, with their sources. ## 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](https://docs.astral.sh/uv/) is the quickest way: ```bash uv tool install 'trading-research-agents[ccxt,openai,anthropic,google,data]' ``` That brings every model provider and every exchange in. Without uv, run `pip install 'trading-research-agents[ccxt,openai,anthropic,google,data]'` inside a virtual environment. To move to the newest release later: ```bash uv tool upgrade trading-research-agents # or: pip install -U 'trading-research-agents[ccxt,openai,anthropic,google,data]' tra --version ``` That is the release, and the version to run. The `develop` branch on GitHub is where the next one is built; a commit there is not a release ([more](#where-it-is-going)). **2. Make a desk.** A desk is a folder holding your settings and everything the agents decide. Name the provider you have a key for: ```bash tra init my-desk --profile autonomous --agent groq cd my-desk ``` | `--agent` | Key in `.env` | Model, when you name none | |---|---|---| | `groq` | `GROQ_API_KEY` (free tier) | `openai/gpt-oss-120b` | | `google` | `GEMINI_API_KEY` | `gemini-flash-latest` | | `anthropic` | `ANTHROPIC_API_KEY` | `claude-opus-5-5` | | `openai`, `deepseek`, `xai`, `openrouter`, ... | see [Models and providers](#models-and-providers) | name one with `--model`; `tra models <provider>` lists them | Add `--venue okx` (or any ccxt id) to trade somewhere other than Bybit. **3. Add your key.** Copy the example file and put your key in it. Every command reads the `.env` next to `strategy.toml` on its own. ```bash cp .env.example .env # then set GROQ_API_KEY=... in .env ``` **4. Check.** `tra check` reads every setting against the others and names the one thing to fix next. A desk that is ready ends with: ``` ok provider groq: ready ready to run `tra run` ``` **5. Run.** `tra run` decides once on live market data, in the sandbox: nothing leaves your machine. `tra run --every 15m` keeps deciding, once per fifteen-minute bar, on the clock. Or type `tra` on its own for the console, which takes the same commands. ```bash tra run tra run --every 15m ``` **6. When you want real orders.** Start on the exchange's demo or testnet API. Make the desk for that exchange from the start, and the rest is three commands: ```bash tra init my-desk --profile autonomous --agent groq --venue bitget cd my-desk # put the exchange's keys in .env beside your model key tra keys --probe --prepare # reads the account; on a demo or testnet sets one-way mode tra mandate --sign "Your Name" --venue-mode tra check ``` `--venue` writes what that exchange needs into `[execution]`: its demo or testnet API, 3x isolated leverage, at most 200 per order, and how its stop and take profit are placed. Change any of it. How to make the key on each exchange is in [Exchange accounts and keys](https://docs.bijectivelabs.dev/opensource/exchange-keys), and [Toward real orders](#toward-real-orders) has the whole path. **What a new desk does before you change anything** | | Default | Where to change it | |---|---|---| | Orders | none: the sandbox writes each decision down and sends nothing | `[execution].mode` | | What it trades | BTCUSDT on Bybit, as a taker | `[run].instrument`, `[universe]`, `--venue` | | Timeframe | decides on 15-minute bars, reads 1h and 4h as context | `[run].bar_interval_s`, `context_intervals` | | Strategy | none fixed: the analyst picks the setup the measured regime supports, or stays flat | `[agents].mechanism` | | Stop and target | the analyst names them; the stop is held between 0.2% and 3% and never inside one ATR, the target between 1.5x and 4x the stop | `[exit]` | | Risk per trade | 0.5% of equity lost at the stop, whatever the stop's distance | `[controls].max_risk_per_trade_bps` | | Bad days | no new entry after a 3% loss on the day or a 10% fall from the peak | `[controls]` | | Time limit | a position closes after 4 hours | `[exit].timeout_bars` | | Trades worth taking | the edge at least 2x the round trip, break even at half the trades or better, at most 6 a day | `[targets]` | | Oversight | a risk manager that can only cut, pause or halt; two auditors that report | `[audit]` | Working on the code itself? See [Development](#development). ## What you see, in order **1. The console.** Run `tra` inside your desk and it opens the console: what is ready, what isn't, and the next command to run. Under it is a prompt that takes every command and draws it right there. Arrow keys go back through what you typed, tab completes, `help` lists the commands and `exit` leaves. For scripts and cron, `tra -c "run --now"` runs one command and exits.  **2. The pass over your instruments.** Type `run --every 15m` and the desk first refreshes any data series that are due, one line each. Then it looks at every instrument on your list, one data pull apiece, and measures it. The screen steps through them live:  **3. One cycle per instrument it takes.** The system found the candidates and measured them; the screener chose among them and cited each instrument's own figures; the system's own order is kept beside the choice. The instruments taken get a full cycle. The terminal shows the whole pipeline from the start and updates it as each step begins and ends. Steps that run at the same time spin at the same time, each with its own clock, and the line underneath says who is working right now:  **4. The result.** When the cycle finishes, the table gives way to the pass over the universe: what the screener took, what waited and what was held, and why. Then the cycle itself: what the analyst proposed and from which figures, and every refusal with the number behind it. Here an ETH short in a ranging market stopped at its exits: with its own stop and target and the round trip, more than half of trades like it would have had to win just to break even:  Then the data the cycle used and how old it was, the series the reading analysts read, the stop and take profit it would have placed, and which agents answered. A cycle that goes further adds what each validator argued, how conviction weighed the analysts, the risk at the stop and the targets:  **5. Between cycles.** The desk says when the next pass is, on the clock and in minutes, for example `next pass at 14:30:00 UTC, in 10m 57s`, and counts down to it. An auditor woken by an alarm gets a spinner of its own. The same cycle as plain text (`--plain`, a pipe or a log), from a real run on live data, shortened: ``` cycle 2026-09-29T02-59-16Z BTCUSDT: 5.344s of agents, 15.042s of validators funding ccxt:bybit age 4.267s ohlcv ccxt:bybit age 32.746s orderbook ccxt:bybit age 7.544s macro risk-off: the operator declared a bullish state for US10Y; measured correlation is neutral (0.0) on a modest sample, weak evidence that does not overturn the declaration sentiment positive: declared state is bullish, and the measured figures both support it technical: long on range_reversion at 0.65 over 5 bars: the close is stretched low in the window read: zscore=-0.587, vwap_gap_bps=-3.99, ret_1_bps=1.59 validator contra oppose on 2 cited figure(s) validator pro support on 3 cited figure(s) conviction: 0.800 of 1.0 (macro 1.0, sentiment 0.5, technical 1.300) risk: 8.29 bps of equity at the stop against the declared 50 bps, size 0.010 cost: 12.87 bps round trip, 2.00 of it estimated gate: 25.0000 bps claimed clears 12.8723 bps cost plus 0.0000 bps margin refused targets: the claimed edge is 1.94x the round trip and the desk declared 2.0x; the cost is certain and the edge is not ``` That trade was refused. It cleared the cost gate and still died, because this desk asks for an edge of twice the cost and got 1.94 times. A refusal names the figure behind it, every time. ## How one cycle decides ```mermaid flowchart TD find[["the system finds the universe and measures each instrument<br/>one data pull each; every value carries its source and age"]] --> wake wake{"trigger<br/>has anything moved since the last look?"} wake -- "no" --> held["held: one data pull, no tokens spent"] wake -- "yes" --> pick["the screener picks among what the system admitted<br/>citing each instrument's own figures"] pick -- "none taken" --> held pick -- "taken" --> briefs briefs["the system writes the briefs<br/>each role sees only the figures its job needs"] --> round1 subgraph round1["asked at the same time"] direction LR tech["technical analyst<br/>a direction, a confidence, a horizon"] macro["macro analyst"] chain["on-chain analyst"] mood["sentiment analyst"] end round1 --> price["the system prices the round trip<br/>fee, spread, impact, funding, slippage"] price --> exits{"the stop and the target<br/>the analyst's levels, held inside your bounds<br/>does the trade break even at half its kind winning?"} exits -- "no" --> refused exits -- "yes" --> round2["validators, as many as you declare<br/>a claim that cites no figure is thrown away"] round2 --> matrix{"confluence<br/>do your declared states agree with the direction?"} matrix -- "no" --> refused["a refusal that names its figure"] matrix -- "yes" --> size["conviction<br/>how much, from your ladder"] size --> risk{"risk per trade<br/>what does it lose at the stop?"} risk --> gate{"cost gate and targets<br/>does the edge clear the cost, by your margin?"} gate -- "no" --> refused gate -- "yes" --> intent["the intent, written into the cycle"] intent --> venue["venue mode only<br/>one order, the stop and take profit attached"] ``` Who does what: | Role | Reads | Answers | Can never | |---|---|---|---| | technical analyst | candles, spread, funding, book imbalance, open interest change, and the regime on its timeframe and the higher ones you declare | a direction, a setup from a fixed list, a confidence, a horizon, and where its stop and target sit | size the trade, place a level outside your `[exit]` bounds, run a trend setup in a range, or fade a market that is not a measured range | | macro analyst | dated rates and levels, dated text | risk-on, risk-off or neutral | propose a direction | | on-chain analyst | chain and derivatives figures | accumulation, distribution or neutral | propose a direction | | sentiment analyst | dated scores and notes you curate | negative, neutral, positive, or not declared | invent a mood no figure supports | | market screener | what the system measured for each admitted instrument: move, spread, regime, volume, correlation to BTC | which instruments to take, in what order, citing their figures | add an instrument the system did not admit | | validators: pro and contra | the proposal and the figures behind it, each without the other's case | the strongest case for or against, as cited claims | see the other side's case, or cite a figure it wasn't given | | validator: neutral, as judge | the same, and both cases once code has checked every claim | support, oppose or abstain, the one verdict that counts | see the advocates' verdicts, or count claims instead of weighing them | | risk manager | what the run recorded: round trips, the losing streak, your limits, the alarm that woke it | continue, cut the size of new entries, pause instruments, or halt, each for a stated number of hours | loosen a limit you set, or add size | | technology and quant auditors | the cycles this desk recorded | findings and proposed changes | change anything | The macro, on-chain and sentiment analysts read dated series you declare under `sources/`. Each one is either a file you keep or a feed the desk refreshes itself (FRED, the Crypto Fear & Greed Index, or any paid vendor that answers JSON over https). `tra sources show` lists every series with where it came from and how old its last value is, and a value older than its `max_age` is shown as stale and never counted. [Data sources](https://docs.bijectivelabs.dev/opensource/sources) has the details. Which validators run is yours to declare. A vote never decides on its own: it moves conviction by the weight you give it (`[conviction].validator_weight`), and a stance counts for what it says beyond its assignment, since a pro that supports is expected to. Analysts are allowed to disagree. Each one's view becomes a score between -1 and 1, computed from its own figures against the lines you drew, so a macro reading barely past its line counts as a small voice and one far past it counts as a big one. Conviction adds them up: agreement grows the size, opposition shrinks it in proportion, and only opposition that outweighs the case stops the trade. A short at 0.70 confidence against a barely bullish macro and sentiment scores 0.56 and trades at half size; against a strongly bullish context it scores 0 and doesn't trade. The technical analyst knows what kind of market it is working in before it decides. The system measures the regime on its timeframe (trending up, trending down, ranging or mixed) and on the higher timeframes you list in `[run].context_intervals`, and it hands over what your macro thresholds say this cycle as well. A setup that doesn't fit the regime, such as a trend trade in a sideways market, is refused by name; `[regime]` holds the lines. Everything after the analysts is arithmetic over numbers you declared. No model can place, cancel or resize an order, read a file outside the project, or edit your configuration. [Agents](https://docs.bijectivelabs.dev/opensource/agents) has the full table of what an agent can reach, and [The cycle](https://docs.bijectivelabs.dev/opensource/cycle) walks through every step. ## Venues A cycle reaches venues through ccxt, so every exchange ccxt supports is already integrated: the same order path, the same gates and the same checks, with nothing in the core naming a venue. What differs from one venue to the next is what ccxt reports it can do, the second column, and how far it has been tested, the last: | Venue | What a cycle can do there | Practice environment | Run end to end by us | |---|---|---|---| | **Bybit** (the default) | everything: orders with the stop and take profit attached | demo, testnet | **yes**, on the demo API: real orders, exits attached, a resting order cancelled | | **OKX** | everything | demo (ccxt's testnet switch) | **yes**, on the demo API: real orders, exits attached, closed by the venue's own exits | | **Bitget** | everything, on a classic or a unified trading account | demo | **yes**, on the demo API, unified account | | **BingX** | everything | demo (VST, ccxt's testnet switch) | **yes**, on the demo API | | **Binance**, **Gate** | orders, with the stop and take profit placed right after the fill (`exits = "separate"`) | demo (Binance), testnet (Gate) | **yes**, on their practice APIs | | WEEX, BloFin, WOO X | everything | testnet | ready for its run | | Hyperliquid, Pacifica, WOOFi Pro, ModeTrade (decentralised) | everything | testnet | ready for its run; [report wanted for Hyperliquid](https://github.com/BijectiveLabs/trading-research-agents/issues/7) | | KuCoin Futures, Deepcoin | everything | none | integrated; no practice environment | | dYdX, Paradex, Extended, Lighter (decentralised); Deribit, Crypto.com, Coinbase International | orders, but no exits at the venue through ccxt, and some cannot set leverage | testnet | not for a desk that needs its exits at the venue | | Kraken, Kraken Futures, Phemex | data for now: ccxt does not report their positions, and no order is sent into a position nobody can see | | | "Everything" means ccxt reports the five things a safe order needs: send it, attach the exits, read the position, read the open orders, cancel. "Run end to end" is the stronger claim, a full run with real orders on the venue's demo or testnet API, and Bybit, OKX, Bitget, BingX, Binance and Gate have had it so far. How to make a key on each is in [Exchange accounts and keys](https://docs.bijectivelabs.dev/opensource/exchange-keys). Any other venue that takes orders can have that run at any time: start on its practice environment, watch a few cycles and read what it sends. Each report moves a venue into the last column. Adding the venue you trade on is four steps, and one command writes most of it: ```bash tra venues okx # what it can do, and which keys it signs with tra venues okx --setup # the blocks to paste into envelope.toml, data.toml, strategy.toml and .env ``` Your fees are filled in from your account when it reports them, and from the venue's standard tier until then, labelled as such; a fee you write yourself is kept and checked against the account. [Venues](https://docs.bijectivelabs.dev/opensource/venues) has the full table, the keys each venue needs, and the four steps. ## Models and providers You choose the provider and the model; nothing is hard-coded. Each provider reads its key from the environment (or the `.env` beside your config) and nowhere else. | Provider | Key in `.env` | Install with | Structured output | Tested live here | |---|---|---|---|---| | `groq` | `GROQ_API_KEY` | `openai` | JSON schema, falling back to JSON mode; checked by the system | **yes**: `openai/gpt-oss-120b` and `openai/gpt-oss-20b`, every live cycle in our records | | `google` | `GEMINI_API_KEY` or `GOOGLE_API_KEY` | `google-genai` | JSON schema | **yes**: `gemini-flash-latest`, as the fallback | | `anthropic` | `ANTHROPIC_API_KEY` | `anthropic` | JSON schema | unit-tested; default model `claude-opus-5-5` | | `openai` | `OPENAI_API_KEY` | `openai` | strict JSON schema | unit-tested | | `deepseek` | `DEEPSEEK_API_KEY` | `openai` | JSON mode | preset only | | `mistral` | `MISTRAL_API_KEY` | `openai` | JSON schema | preset only | | `xai` | `XAI_API_KEY` | `openai` | JSON mode | preset only | | `openrouter` | `OPENROUTER_API_KEY` | `openai` | JSON mode | preset only | | `qwen` | `DASHSCOPE_API_KEY` | `openai` | JSON mode | preset only; pass `--base-url` for your region | | `ollama` | none | `openai` | JSON mode | preset only; a local server | | `local` | none | `openai` | JSON mode | any OpenAI-compatible server; pass `--base-url` | | `9router` | `9ROUTER_API_KEY` | `openai` | JSON schema | preset only; a local router | Whatever the provider, every answer is parsed against a closed schema by the system before anyone reads it, so a model that only offers JSON mode is held to the same shape as one with strict schemas. ```toml [agents] provider = "groq" model = "openai/gpt-oss-120b" effort = "medium" # minimal | low | medium | high | xhigh | max, where the # vendor takes it; left out, the vendor's default applies fallback = ["google:gemini-flash-latest", "anthropic:claude-opus-5-5"] [agents.roles.sentiment_analyst] # a role that only labels can run on a cheaper model model = "a-cheaper-model" effort = "low" ``` `fallback` is tried in order when a provider is rate limited or down, with the same brief. A vendor's free tier meters each model on its own, so roles can share a provider across two models and each model keeps its own allowance; `tra check` judges the load per model and says when one is too much. Every call is a line in `usage.jsonl` with its tokens and latency, and nothing caps spend unless you declare a ceiling. `tra keys --probe` proves each key works without sending a prompt. A vendor of your own is about thirty lines ([Model providers](https://docs.bijectivelabs.dev/opensource/providers)). ## Toward real orders What it trades today, through one order path and the same gates: - **Linear perpetuals** (USDT- or USDC-margined swaps) on any venue ccxt reaches, long and short, with the leverage and margin mode you declare. The default, run end to end on six exchanges. - **Spot pairs**, long only and paid in full, for a desk that lists `spot` in `[execution].markets`. - **Stock perpetuals and tokenized stocks**, which are a perpetual and a spot pair to the venue, with the underlying exchange's hours respected. - **Prediction market outcomes**, for a desk that lists `prediction`, decided on a probability by their own analyst and priced to resolution. That is where the project started, not where it stops. For spot, [Venues](https://docs.bijectivelabs.dev/opensource/venues#where-an-order-goes-and-what-an-instrument-is) says how to set a desk up. Spot, a stock perpetual and a tokenized stock have been run on the Bybit and OKX demos; prediction outcomes have run in sandbox on live data, and their order path is tested against ccxt's shapes until a practice venue is run. Dated futures, inverse contracts and options are on the way, each with its own cost model, exit rules and tests. Until a market type has those, venue mode checks the type on every order and refuses it, because a market the system cannot yet price and protect is not one it should send to. [Boundaries](https://docs.bijectivelabs.dev/opensource/boundaries) says what each one takes. An agent desk goes through three steps, and you can stay at any of them as long as you like: | Step | How | What happens | Needs | |---|---|---|---| | 1. Sandbox | `tra run` | the full cycle on live data; every decision written down, no order sent | a model key | | 2. Demo or testnet API | `tra run` with `[execution].mode = "venue"` and `environment = "demo"` or `"testnet"` | real orders on the exchange's demo or testnet API, exits attached, positions looked after | a signed mandate, a leverage, `max_notional`, practice keys | | 3. Real capital | the same, with `environment = "mainnet"` | real orders with real money | all of the above, plus the ladder at its canary tier (`tra ladder promote`, with evidence) | Steps 1 and 2 have been run end to end on the demo or testnet APIs of Bybit, OKX, Bitget, BingX, Binance and Gate. Step 3 has not been run by us; treat it as yours to verify, small, first. If you bring a scripted strategy of your own instead of the agents, it has a research path of its own before any of this: `tra data get BTCUSDT 2025-01-01` and `tra backtest` replay a day of the exchange's archive net of every cost, `tra paper --minutes 30` runs it on the live feed with nothing sent, and `tra live` is a small canary session behind hard caps. The example core is there to show the path, not to make money, and the replay prints its net as it comes out, loss or gain. [The live tier](https://docs.bijectivelabs.dev/opensource/live) has the details. Venue mode is the only mode that can lose money, so it has a door in front of it. Read the mandate with `tra mandate`; when you accept it, `tra mandate --sign "Your Name"` keeps it in the project as `MANDATE.md` and signs `[execution]` with your name and today's date, in one step. Signing alone does not switch anything on; `--venue-mode` signs and turns orders on together. `tra check` names whatever else is missing. ### Your money, your orders, your positions Once orders flow, three things look after the money, all of them the system's own rules and none of them a model: | Before an order | When it is sent | While it is open | |---|---|---| | the account's real equity and free margin are read | your leverage is applied at the venue and read back | at the start of every pass, each position is checked against the venue | | sizing uses the smaller of the real equity and what you allow the desk | an order whose liquidation would sit inside its stop is refused | one that outlives its hold limit is closed with a reduce-only order | | an order may use only part of the free margin | a taker entry is a limit IOC within your slippage band, never a naked market order | one the venue's stop or take profit closed is written up with its real fees and funding | | a day's loss past your limit stops new entries | the stop and take profit go with the entry, so they outlive this process | the kill switch flattens everything before the desk stops | Who decides what, in one line each: **the analysts propose the direction, your risk rule sets the size, you choose the leverage, and no model touches the last two.** Leverage never makes a trade bigger. It only decides how much margin the trade ties up and how far away liquidation sits. ```toml [execution] mode = "venue" environment = "demo" # demo | testnet | mainnet leverage = 3 # yours to choose; it never makes a trade bigger max_notional = 400 # the most one order may be worth, in quote currency margin_mode = "isolated" # isolated | cross hold_limit = "timeout" # close by time after [exit].timeout_bars; or horizon, or none ``` Underneath, on every venue: the order goes only to the environment you declared (demo, testnet or mainnet); an open position or a working order refuses a second entry; a size off the venue's step is refused rather than rounded; a clock more than a second off the venue's refuses before anything is signed; and Ctrl-C or a service stop cancels a resting order before the process leaves. Every close goes to `positions.jsonl` and every finished trade to `round_trips.jsonl`. [Capital, orders and positions](https://docs.bijectivelabs.dev/opensource/capital) has every setting, every refusal and the arithmetic behind each one. One thing to know before you rely on it: the position checks run at the start of each pass of `tra run --every`. With no desk running, an open position has its venue-side stop and take profit and nothing else, so a desk meant to run unattended belongs under a supervisor. Orders cross the book by default (`taker-taker`): they always fill, which is how most desks trade. Point `[run].venue_key` at a `maker-taker` channel and entries rest on the book as post-only orders instead - a lower fee, fewer fills, since a resting order can be left behind by the market. Either way the cost gate prices the fee of the channel you chose. ## Watching a desk, and what is kept The console runs commands in its own process, so closing it ends what it was running. A desk that should keep running belongs under a supervisor (systemd, a service manager, `tmux`), and then you look at it from anywhere with: ```bash tra watch --every 5s # a read-only view built from the records the desk writes ``` `tra watch` opens no connection, holds no key and takes no lock, so opening and closing it does nothing to the desk. What is kept, and where: | What | Where | Notes | |---|---|---| | everything one cycle did | `runs/cycles/<id>/` | snapshot, briefs, answers, intent, `placed.json`, `cycle.json`, and `inputs.json.gz` with the raw inputs; `cycle.json` holds a sha256 of each file | | the pass over the universe | `runs/screens/` | every instrument measured, what the screener chose and why | | every model call | `runs/cycles/usage.jsonl` | tokens, latency, price | | when the desk ran and what stopped it | `runs/cycles/scheduler.jsonl` | one line per start and stop | | every position closed, by time, by the venue or by the kill switch | `runs/cycles/positions.jsonl` | venue mode | | every finished trade with entry, exit, fees and funding | `runs/cycles/round_trips.jsonl` | venue mode; what the quant auditor reads | | the first equity reading of each day | `runs/cycles/equity.jsonl` | what the daily loss limit is measured from | | what you typed at the prompt | `.tra-history` | a convenience only; `tra -c` keeps none | ## Command line Every command says what it did. Exit code 0 means cleared, 1 means a gate said no, 2 is a usage error. `--json` gives machine-readable output and `--plain` gives text instead of panels. **Getting started** | Command | What it does | |---|---| | `tra` | opens the console | | `tra init my-desk --profile autonomous` | a project wired for the agents, every file commented | | `tra check` | every setting read against the others, with what to fix | | `tra keys --probe` | proves every key works; no key is printed, no prompt or order sent | | `tra models groq` | the models your key can use on a provider, read from the vendor; no prompt sent | | `tra init my-desk --profile autonomous --venue okx` | a desk wired for one exchange: data, orders, demo or testnet API, keys | | `tra venues` | every venue the docs describe, and what each can do | | `tra venues okx --setup` | what a venue can do, and the blocks to paste to trade on it | | `tra mandate` | the text venue mode requires; `--sign "Your Name"` keeps it as `MANDATE.md` and signs `[execution]` in one step | **Running** | Command | What it does | |---|---| | `tra run` | one autonomous cycle | | `tra run --every 15m --cycles 12` | twelve scheduled passes: the first now, then one on every fifteenth minute of the clock | | `tra run --now` | ask the roster even if the trigger would have held a quiet market | | `tra watch --every 5s` | a read-only view of a running desk | | `tra audit` | both auditors over the records; nothing is applied | | `tra backtest`, `tra paper`, `tra live` | replay, shadow, canary | **Data** | Command | What it does | |---|---| | `tra data get BTCUSDT 2025-01-01` | download a day, verify its checksum, audit it, write Parquet and funding | | `tra data audit export.csv --mapping mapping.toml` | your own CSV or Parquet, through the same audit | | `tra data pull BTCUSDT` | one live snapshot through the chains in `data.toml` | | `tra sources show`, `tra sources pull` | where the reading analysts' series come from and how old they are; refresh them now | | `tra sources add macro us10y --from fred --id DGS10 --high bearish` | a series onto the shelf in one step: pulled now, its lines drawn from its own history | | `tra universe` | which perpetuals discovery finds on the venue now, and what each filter took out | | `tra runs verify` | every cycle's files against their hashes, and its briefs against its raw inputs | | `tra runs prune --keep 90d` | what old cycle directories would be removed; add `--yes` (and `--archive`) to do it | **The ladder, research and hosts** | Command | What it does | |---|---| | `tra ladder show`, `promote`, `demote` | which tier the desk stands at; one step up with evidence, or down | | `tra chain floor`, `observe`, `check`, `validate` | the research chain, layer by layer ([The falsification chain](https://docs.bijectivelabs.dev/opensource/chain)) | | `tra ledger show` | every idea that died, and what killed it | | `tra agent session`, `eval`, `trace` | the research session, model comparison, a run read back | | `tra mcp serve` | the read-only gates as tools for any MCP host | ## What it guarantees, and what is not built yet Some rules are guarantees, enforced by the system and tests, and every change has to keep them: - **No model touches an order or a key.** Models read figures and answer; the system sizes, prices, limits and sends. - **No model can loosen a control.** A model can tighten a limit, step the ladder down or arm the kill switch; never widen, promote or disarm. - **One decision, at most one order.** A venue error is recorded and the next cycle decides again; nothing is retried around real capital. - **Stale or missing data is refused,** never read as zero or as current. Other things are simply not built yet, and contributions are welcome: inverse, dated futures and options; on-chain venues outside ccxt; more than one account; transfers and treasury; routing and execution algorithms; portfolio accounting. [Boundaries](https://docs.bijectivelabs.dev/opensource/boundaries) lists each one with what it does today and what a contribution would need. The example strategy cores are examples: your edge is yours to declare. [Liability](https://docs.bijectivelabs.dev/opensource/liability) says plainly where responsibility sits when real capital is involved. ## Where it is going The project is in active development, and what this page describes is where it stands today, not where it stops. - **More market types.** Spot, stock perpetuals, tokenized stocks and prediction markets are built; inverse and dated futures and options follow, each added with its own cost model, exit rules, sizing and tests before venue mode accepts it. - **More venues run end to end.** Every venue ccxt supports already goes through the same order path and gates. Each one joins the six already in the last column of the venues table after a full run on its demo or testnet API, ours or yours. - **The rest of the not-built-yet list,** one piece at a time, without weakening a guarantee. **Use the release.** What PyPI installs is the latest release, and it is the version to run. Releases come from `master`. The `develop` branch is where the next release is built: it moves often, a commit there is not a release, and it can carry work that is unfinished or changed again before it ships. A set of changes becomes a release when it is merged into `master`, tagged and published, and [CHANGELOG.md](https://github.com/BijectiveLabs/trading-research-agents/blob/master/CHANGELOG.md) says what each one brought. ## Documentation The full documentation is at [docs.bijectivelabs.dev](https://docs.bijectivelabs.dev). Its source is in `docs/`, so a change in behaviour and the page that describes it go in the same pull request. | Read this | For | |---|---| | [Why it is built this way](https://docs.bijectivelabs.dev/opensource/why) | the documented failures it is built against, each with its source, and what we found building it | | [The cycle](https://docs.bijectivelabs.dev/opensource/cycle) | the cycle step by step, and every setting that shapes it | | [Agents](https://docs.bijectivelabs.dev/opensource/agents) | each role, what it reads, and what an agent can and cannot reach | | [Data sources](https://docs.bijectivelabs.dev/opensource/sources) | where the macro, on-chain and sentiment figures come from, fetching them, and freshness | | [Capital, orders and positions](https://docs.bijectivelabs.dev/opensource/capital) | equity, margin, leverage, liquidation, daily loss, time exits, the kill switch, and the records they leave | | [Venues](https://docs.bijectivelabs.dev/opensource/venues) | which venues work, and adding yours | | [Working with language models](https://docs.bijectivelabs.dev/opensource/llm), [Model providers](https://docs.bijectivelabs.dev/opensource/providers) | how models are used: fallback, spend, adding a provider | | [The live tier](https://docs.bijectivelabs.dev/opensource/live), [The trading agent](https://docs.bijectivelabs.dev/opensource/trading) | the ladder from replay to a live session | | [Your own data](https://docs.bijectivelabs.dev/opensource/your-data), [The data gate](https://docs.bijectivelabs.dev/opensource/data) | trade history, series and vendor feeds you bring, in CSV, JSON or Parquet, and the checks every file passes | | [Boundaries](https://docs.bijectivelabs.dev/opensource/boundaries), [Liability](https://docs.bijectivelabs.dev/opensource/liability) | what is guaranteed, what is not built yet, and who is responsible | | [The agent](https://docs.bijectivelabs.dev/opensource/agent), [The MCP server](https://docs.bijectivelabs.dev/opensource/mcp) | the research agent, and the MCP server | | [Architecture](https://docs.bijectivelabs.dev/opensource/architecture) | packages, import rules, file formats | | [The falsification chain](https://docs.bijectivelabs.dev/opensource/chain), [Execution realism](https://docs.bijectivelabs.dev/opensource/execution), [The kill ledger](https://docs.bijectivelabs.dev/opensource/ledger) | the research chain, execution realism, verdicts | | [Command line](https://docs.bijectivelabs.dev/opensource/commands) | every `tra` command | | `CHANGELOG.md` | what changed | ## Development ```bash git clone https://github.com/BijectiveLabs/trading-research-agents && cd trading-research-agents uv sync --all-extras uv run ruff check . && uv run ruff format --check . uv run mypy uv run pytest ``` [CONTRIBUTING.md](https://github.com/BijectiveLabs/trading-research-agents/blob/master/CONTRIBUTING.md) has the branch flow and the standards the code is held to. ## Where it comes from This repository opened to the public in October 2026. Its history starts on 12 September 2026, when the code was separated from Bijective's internal work, and every commit, tag and contributor since then is here. The ideas it is built on are older: the falsification chain, the cost model and the controls in front of every order come from Bijective's research and from the trading platform it was building before this repository existed. The language-model agents came later and sit on top of those gates, which is why they can propose but never size, price or send. ## License MIT. See [LICENSE](https://github.com/BijectiveLabs/trading-research-agents/blob/master/LICENSE); [NOTICE](https://github.com/BijectiveLabs/trading-research-agents/blob/master/NOTICE) lists the third-party software this package builds on. Built by [Bijective Labs](https://github.com/BijectiveLabs).