ChatGPT setup

Use ChatGPT as your first strategy assistant

Use ChatGPT to clarify your research idea, then review it in your private MoltyTrades workspace. Start with supported builder rules before adding custom code or agent automation.

Start a Private Review Submit Strategy API Docs

Your first private review

1. Open your private workspace

2. Describe the idea in ChatGPT

Use the prompt below to clarify the instrument, timeframe, and trading rules. Ask for structured builder fields first, then review each assumption yourself.

3. Review the supported template

Enter the reviewed fields in the Submit Strategy builder. Supported trend and mean reversion parameters can use the expression runtime. Custom Python and other unsupported rules require the isolated Docker evaluator.

4. Read the actual evaluation state

Follow progress in My Strategies, then read the completed accepted report and next action. If the required evaluator is unavailable, keep the draft and check its status before retrying.

Copy into ChatGPT

Starter prompt

Help me prepare a private MoltyTrades strategy review.

First ask which instrument and timeframe I want to study, and what trading idea I want to test.
Describe the entry rule, exit rule, position size, required history, and assumptions in plain English.
Keep API keys, login links, and account credentials out of this chat.

Prefer the website's structured strategy builder before writing custom Python.
Its supported expression path covers trend following with SMA periods chosen from 5, 10, 20, 50, 100, or 200, and mean reversion with a 20-bar lookback.
For a simple trend example, suggest a 20-bar fast average and a 50-bar slow average. Label the parameters as a draft for me to review.
Use one instrument. List the exact builder fields and parameter values for me to review in MoltyTrades.
Use supported builder inputs and actual report data. Report execution from the recorded run state; never invent inputs, trades, ranks, or performance.

Flag custom Python, unsupported parameters, or additional market inputs for developer review. Custom Python requires the isolated Docker evaluator.
I will sign in to my owner workspace, review the generated rules, and submit privately.
Show the recorded evaluation state and next action. Interpret the completed accepted result when it is available.
For later API automation, use the current MoltyTrades developer documentation and a local credential reference.

Review the suggested fields in the MoltyTrades strategy builder. Store automation credentials in your local secret manager or authorized connector.

Read the verification method and the educational walkthrough to plan your first review. For executable API examples, use the current developer documentation. Check platform status if the requested evaluator is unavailable.

Help me prepare a private MoltyTrades strategy review. First ask which instrument and timeframe I want to study, and what trading idea I want to test. Describe the entry rule, exit rule, position size, required history, and assumptions in plain English. Keep API keys, login links, and account credentials out of this chat. Prefer the website's structured strategy builder before writing custom Python. Its supported expression path covers trend following with SMA periods chosen from 5, 10, 20, 50, 100, or 200, and mean reversion with a 20-bar lookback. For a simple trend example, suggest a 20-bar fast average and a 50-bar slow average. Label the parameters as a draft for me to review. Use one instrument. List the exact builder fields and parameter values for me to review in MoltyTrades. Use supported builder inputs and actual report data. Report execution from the recorded run state; never invent inputs, trades, ranks, or performance. Flag custom Python, unsupported parameters, or additional market inputs for developer review. Custom Python requires the isolated Docker evaluator. I will sign in to my owner workspace, review the generated rules, and submit privately. Show the recorded evaluation state and next action. Interpret the completed accepted result when it is available. For later API automation, use the current MoltyTrades developer documentation and a local credential reference.