The trading team · Guide 00
Start here: how this library works
In one lineThis library explains how an AI agent trading team works, with the research frameworks, tools and prompts behind it. Open any guide, in any order.
What you'll get
- What this library is, and what it deliberately is not.
- How the shelves are laid out, and how to set up your own AI library assistant in two minutes.
- What the system needs to run.
- Where the research team and the team kit fit.
- A sample build order, one small job per step.
1What this library is
You already trade. You have a setup you like, a platform you know and probably a chat AI you use now and then: "what do you think of this chart?"
That is one opinion from one chat that wants to be helpful. It agrees too easily, it invents levels, and it has no idea what your rules are.
This library shows how to turn that habit into a team: AI agents, each with one job, one format and only the information it should see. An Analyst describes the market. A Researcher turns your setup into rules you can check. A Bull and a Bear argue both sides. A Risk Manager says no when your rules say no. A Trader writes the trade card. A Decider writes a one-page memo with a score from a fixed rubric.
Then the risk gate checks the plan, and the execution agent places the order automatically through your broker or prop API, only inside your risk limits. You set the rules and limits. The system executes.
2What it is not
- Not signals. Nobody here tells you what to trade. The team checks your setup against your rules.
- Not a black box. Every agent, prompt and rule is written out here. The research seats run in chat tools you already use: Claude, ChatGPT, Gemini, or the AI inside your workspace. Execution runs through a broker or prop API, inside hard limits.
- Not a strategy to copy. The playbooks in Guides 12 and 13 are research briefs with blanks. You fill the blanks and test them on your own market. No brief comes with a result.
- Not a promise. A better process doesn't guarantee a better result. The team helps you skip the trades your own rules say to skip. The market still decides the outcome.
If you want a magic signal, this is the wrong place. If you want a trading system with a team of agents and hard rules behind it, read on.
3How to use the board
The library has three shelves.
The trading team, Guides 00 to 10. How the system works, start to finish. Each guide has the same shape:
- In one line and What you'll get, so you know why you're reading it.
- Numbered sections, a worked example on a realistic setup (NQ futures or EURUSD, prices marked "example"), and red flags where the AI tends to go wrong.
- Common mistakes and a checklist.
Playbooks, Guides 11 to 13. The research team. Guide 11 is the method for testing a strategy idea honestly. Guides 12 and 13 cover eight well-known public strategy families written as research briefs. Use them to pressure-test your own setup or look at a new one, away from the trading session.
The team kit, Guides 14 to 17. The tools the team runs on, every ready-made prompt in one place, every template, and a glossary.
4Set up your AI library assistant (2 minutes)
You can set up an AI research assistant that answers from this library, inside the AI you already use. It tells you which guide each answer comes from.
- Download the two assistant files from the Templates page:
ai-trading-library-full.md(the whole library in one file) andresearch-assistant-instructions.txt. - In Claude, create a Project (in ChatGPT, a Project or a custom GPT). Paste the assistant instructions into the project's instructions and upload the library file as its knowledge.
- Ask it your first question.
Use it for:
- "Where does the Bear get its information from?"
- "My Risk Manager cleared a trade that was over my limit. What went wrong?"
- "Help me rewrite my setup description so the Researcher can turn it into rules."
It will not tell you whether to take a trade, what the market will do, or which firm to pick. That's by design. Ask it about the method, not the market.
5What you need
| You need | Why | Notes |
|---|---|---|
| One AI chat account that reads images | Every role runs here | A paid plan is easier: free tiers limit messages and image uploads |
| Your charting platform | Screenshots and, later, exported data | Whatever you use now |
| An economic calendar you trust | The team only knows the events you paste | Copy as text each morning |
| A spreadsheet or table | Your journal | Columns are given in Guide 08 |
| A broker or prop account with API access | The execution agent sends orders here | Set hard limits on the account too |
| A demo or sim account | Run the full system with no money on the line first | Strongly recommended |
Guide 14 lists the whole kit by job, with a free minimum version and a two-minute setup step for each tool.
6A sample build order
| Step | Job | Guide | Time |
|---|---|---|---|
| 1 | Check your kit, set up your workspace, paste the team setup, write your setup in your own words | 01, 02, 14 | 30 min |
| 2 | Build an event sheet from yesterday's calendar. Run the Analyst and Researcher on yesterday's chart. Build your setup sheet | 03 | 30 min |
| 3 | Run the Bull and the Bear on the same chart, in separate chats. Then a pre-mortem | 04 | 20 min |
| 4 | Write your risk rules sheet and your tilt-check rule. Set the matching limits in your platform | 05, 07 | 40 min |
| 5 | Trade card and decision memo on a past day. Then the full routine on a replay | 05, 06 | 30 min |
| 6 | The full routine on a live session, on demo or sim, with the execution agent on. Debrief afterwards | 06, 08 | 25 min |
| 7 | First review of the journal, even with only a few rows | 08 | 30 min |
Prop-firm traders add Guide 09 at step 4.
After that. Keep the system running. Then read Guide 11 and run the Evidence Checker on whatever rows you have. It will tell you, correctly, that it is too early to conclude anything, and show you what to collect. Guide 10 covers how the system runs itself end to end.
7Worked example: one trader's build
Illustrative. A trader who trades MNQ in the first two hours of the New York session.
- Step 1. Creates a workspace called "Team", pastes the team setup, and writes: "I buy when NQ breaks the opening range and comes back to retest it with a strong candle, when the trend is up."
- Step 2. The Researcher finds three vague words: "strong", "trend" and "comes back". They become measurable rules. The setup sheet is half a page.
- Step 3. The Bear points out that the retest sits 40 points under the prior day's high. Nobody had looked up.
- Step 4. Writes ten risk rules and finds the platform has a daily loss limit setting that was never switched on. Switches it on.
- Step 5. Runs the full team on last Tuesday's chart. It takes 26 minutes. Fine for a first run.
- Step 6. Live, on sim. 17 minutes. The event sheet shows a release inside the window, the Decider scores the plan 2, and the system passes. No order is sent. That counts.
- Step 7. Four journal rows. The reviewer says: "sample too small to conclude anything", and points out one trade sent without a memo. One rule change: no order without a memo.
Results aren't the point of a first run. A working routine is.
8Common mistakes
- Reading everything before building anything. Build each piece as you read about it. The team is a routine, not a theory.
- Jumping to the prompts without a rules file. Without your rules, every seat is guessing. The team is only as good as what you give it.
- Starting with the playbooks. They are the most interesting guides and the wrong place to begin. Build the routine first.
- Going live straight away. Run the full system on demo, sim or replay first.
- Changing everything at once. New tool, new setup, new routine and new risk rules at once means you can't tell what helped.