AI Guide Map
Pattern library

Exchange Integration Pattern Library

Reusable blueprints for building cryptocurrency exchange integrations. Pick the pattern that matches the workflow, then open an implementation guide when Binance, Bybit, or another exchange needs exact SDK calls, request fields, event topics, or error handling.

Default Scope

  • Audience: developers and AI coding agents building cryptocurrency exchange integrations
  • Runtime: Node.js LTS with TypeScript recommended
  • Packages: selected exchange SDK for the selected venue
  • Execution: DEMO, TESTNET, and LIVE remain disabled by default until the selected EXECUTION_MODE value is explicitly configured and all required gates pass.

Starter Patterns

WorkflowUse CaseGuidance
Historical Backfill with Live WebSocket StreamsBackfill historical data and keep in sync using live streamsUse an exchange-specific candle implementation when exact SDK fields are needed; Binance and Bybit examples are tested overlays, not the only valid candle venues.
Exchange State ManagementTrack and react to account state changes, such as position updates (new/increased/reduced/closed). React to position changes, placing/amending/cancelling TP/SL/DCA orders after fills.Open the exchange implementation for SDK clients, topics, fields, and rejection codes.
Order Intent Chasing with Exchange APIs & WebSocketsApproved order intent follows the price with a maker order to fill as soon as possible.Keep signal generation and risk approval outside the execution adapter.
Stop Loss using Conditional Algo Orders with Binance USD-M APIs & WebSocketsExact Binance USD-M conditional order fieldsUse alongside Exchange State Management for account-state workflows.

Core patterns

Reusable exchange-neutral lifecycles. Start here before choosing exchange-specific request fields.

Execution adapters

Use after a strategy, operator, or risk layer has already approved an order intent.

Exchange implementations

Exchange-specific pages apply a core pattern to concrete SDK methods, request fields, topics, product names, and error handling.

Exchange request shapes

Focused exchange semantics for request builders and validation rules.

Agent artifacts

Machine-readable entry points for generators and coding agents.

Implementation Steps

Follow these in order; use the linked artifacts only where they clarify the current step.

Combining Patterns

Most real systems use more than one pattern. A strategy can consume a historical backfill plus live stream pipeline, emit approved intents, and pass them to an execution adapter. A position manager can track exchange state and react to position changes to manage TP/SL/DCA order mechanics.

  • Choose one owner for account state, order ownership, and private-event ingestion.
  • Use implementation guides for exchange-specific SDK details before writing request builders.
  • Keep the write-capable EXECUTION_MODE values DEMO, TESTNET, and LIVE disabled by default until credentials, configuration, exchange rules, venue routing, and local validation have been reviewed.
  • Trace the lifecycle chain for each pattern before connecting it to another pattern.
  • Add fixtures for cross-boundary handoffs such as data-ready -> signal, signal -> approved intent, and approved intent -> execution adapter.

Use Patterns Safely

  • Choose a pattern by lifecycle: historical backfill plus live streams, exchange state management, execution, or exact request shape.
  • Read the matching exchange implementation before coding SDK calls, request fields, event topics, product modes, or error handling.
  • Keep account-state ownership, Custom Order ID ownership, and private-event ingestion explicit when combining modules.
  • Fixture or replay coverage must match each lifecycle claim; unsupported behavior should be named as unsupported.
  • Keep the write-capable EXECUTION_MODE values DEMO, TESTNET, and LIVE disabled by default until credentials, config, exchange rules, venue routing, and local validation have been reviewed.

Disclaimer: AI is an exciting and promising technology, but content, prompts, code, examples, strategy ideas, and tool outputs produced with AI can be incomplete, incorrect, insecure, outdated, or unsuitable for your circumstances. Anything produced from these prompts or from any AI coding agent must be independently reviewed by qualified professionals before use. You are responsible for testing, security review, compliance review, exchange-rule review, credential controls, trading-risk controls, and any decision to deploy or rely on the resulting work. Siebly provides this page and generated prompt text for informational purposes only. They are not financial, investment, legal, security, compliance, or professional engineering advice. To the maximum extent permitted by law, Siebly accepts no responsibility for losses, claims, damages, failed orders, missed trades, security incidents, regulatory issues, or other consequences arising from AI-generated output, your prompts, your code, your trading strategy, or your implementation decisions.