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Writing trading code with AI assistance is increasingly common, but large language models often hallucinate method names, invent parameter shapes, or produce outdated patterns when working with specialised libraries. The gateio-api SDK ships a dedicated llms.txt file designed to give any LLM or AI coding assistant the exact context it needs to produce accurate, working code on the first attempt.

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What Is llms.txt?

llms.txt is a single machine-optimised text file that packages the most important parts of the gateio-api repository into a compact, structured format. It is generated using Repomix and contains:
  • The full directory structure of the SDK
  • All TypeScript source files for REST and WebSocket clients
  • Complete function signatures, parameter types, and JSDoc comments
  • Request and response type definitions for every Gate.com API endpoint
  • Working examples from the examples/ directory
The file is intentionally structured for machine consumption — not for humans reading sequentially — which means it avoids prose filler and presents code and type information as densely as possible. The first lines of llms.txt describe its format and purpose: 
This file is a merged representation of a subset of the codebase, containing
files not matching ignore patterns, combined into a single document by Repomix.
The content has been processed where content has been compressed (code blocks
are separated by ⋮---- delimiter).
...
Purpose:
--------
This file contains a packed representation of a subset of the repository's
contents that is considered the most important context.
It is designed to be easily consumable by AI systems for analysis, code review,
or other automated processes.

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Where to Find llms.txt

The file is bundled with every published version of the package and is available in two places:
LocationHow to access
npm packagenode_modules/gateio-api/llms.txt after npm install gateio-api
GitHub repositorygithub.com/tiagosiebler/gateio-api/blob/master/llms.txt
The package.json files field explicitly includes llms.txt so it is always present in the installed package: 
"files": [
  "dist/*",
  "llms.txt"
]

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Why Use It?

Without llms.txt in context, an LLM generating Gate.com trading code typically:
  • Invents method names that do not exist (client.createOrder() instead of client.submitSpotOrder())
  • Gets parameter shapes wrong (wrong field names, missing required fields)
  • Confuses Gate.com’s WebSocket subscription model with other exchanges
  • Generates authentication code that does not match Gate.com’s HMAC-SHA512 signing scheme
With llms.txt loaded into context, the same model can produce accurate, ready-to-run code using the real SDK signatures.
When asking an AI coding assistant to help write Gate.com trading code, always include llms.txt in the context window first. This single step dramatically reduces hallucinations and ensures the generated code uses the correct method names, parameter shapes, and patterns from the actual SDK.

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How to Use llms.txt with an AI Coding Assistant

1

Get the llms.txt file

After installing the package, the file is available locally:
npm install gateio-api

# The file is now at:
cat node_modules/gateio-api/llms.txt
Or download it directly from the GitHub repository.
2

Load it into your AI tool's context

How you load the file depends on which tool you are using:Cursor IDE — Add the file as a “Doc” or drag it into a Composer chat window. You can also reference it with @llms.txt if it is in your workspace.GitHub Copilot — Open the file in the editor before asking Copilot to generate code. The open file is automatically included in the model’s context.Claude / ChatGPT / other chat interfaces — Paste the file contents directly into the conversation, or attach it as a file upload if the interface supports it.Continue.dev — Add llms.txt as a context provider in your .continue/config.json.
3

Ask your question with the context loaded

With llms.txt in context, you can ask natural-language questions and receive accurate SDK code:
Using the gateio-api SDK (context provided in llms.txt), write a function
that subscribes to the BTC_USDT spot order book WebSocket stream and logs
each update.

Using the gateio-api SDK, show me how to place a limit order on the
perpetual futures market for BTC_USDT with a stop-loss, using the
correct parameter names.
4

Verify the generated code

Always review AI-generated trading code before running it with real funds. Even with llms.txt in context, verify that:
  • Parameter names match the TypeScript type definitions in the SDK
  • Order sizes and prices match Gate.com’s precision requirements for your instrument
  • Error handling is in place (see the Error Handling guide)

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What the File Contains

llms.txt covers over 16,000 lines of compressed source context, including:
  • src/RestClient.ts — All REST API methods across spot, futures, delivery, options, margin, CrossEx, Alpha, and OTC markets
  • src/WebsocketClient.ts — All WebSocket subscription topics and WebSocket API methods
  • src/WebsocketAPIClient.ts — The promise-based WebSocket API client
  • src/types/request/ — TypeScript interfaces for every REST request parameter
  • src/types/response/ — TypeScript interfaces for every REST response body
  • src/types/websockets/ — WebSocket event and request types
  • examples/ — Working code examples for REST and WebSocket usage
The format uses ⋮---- delimiters between compressed code sections, which helps LLMs with limited context windows process the file efficiently without token-wasting blank lines.

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Benefits at a Glance

Without llms.txtWith llms.txt
Hallucinated method namesReal method names from the source
Wrong parameter field namesExact TypeScript interface fields
Generic authentication boilerplateSDK-specific HMAC-SHA512 signing
Outdated WebSocket patternsCurrent subscription model
Requires multiple correction roundsAccurate code on the first attempt
The llms.txt file is regenerated with each SDK release to reflect the latest method additions and type changes. If you cached a copy from an older version of the package, update it when you upgrade gateio-api.

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