API & Integration Building

API Integration Spec Writer

Turns a description of two systems that need to talk to each other into a complete integration spec — auth method, data flow, sync logic, and failure handling.

Last updated Jul 11, 2026
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TL;DR

API Integration Spec Writer is a free AI skill for api & integration building. Turns a description of two systems that need to talk to each other into a complete integration spec — auth method, data flow, sync logic, and failure handling. It works with Claude, ChatGPT, Cursor and is ready to use out of the box.

Download Skill.md Package

About this skill

API Integration Spec Writer takes a plain description of two systems that need to be connected (e.g. 'sync new Shopify orders into our internal fulfillment system') and produces a full technical integration spec: authentication approach, data flow direction, field mapping, sync frequency/triggering logic, and failure/retry handling. It's built for developers and technical product managers who need to scope an integration project before writing code, ensuring nothing critical (like idempotency or rate limits) gets missed.

What it does

Given a description of two systems and the desired data flow, the skill outputs an integration spec covering authentication, data flow direction, field mapping, sync triggering logic, and failure/retry/idempotency handling.

What is included

  • Authentication approach recommendation
  • Data flow direction and field mapping
  • Sync triggering logic (webhook vs polling) with rationale
  • Idempotency and failure/retry handling
  • Rate limit and error handling considerations

How to use it

1. Download the SKILL.md file
2. Upload it to a new Claude conversation
3. Describe the two systems and what data needs to flow between them
4. Receive a complete technical integration spec

Examples

Example input
We need new orders from Shopify to automatically create fulfillment records in our internal warehouse system.
Example output
INTEGRATION SPEC: Shopify → Internal Warehouse System

AUTHENTICATION: Shopify Admin API using OAuth 2.0 access token scoped to read_orders; store token securely in secrets manager, not in code.

DATA FLOW: One-directional, Shopify → Warehouse System (no write-back to Shopify needed for this use case).

TRIGGERING LOGIC: Use Shopify's orders/create webhook rather than polling — lower latency, avoids unnecessary API calls against Shopify's rate limits.

FIELD MAPPING:
Shopify order.id → Warehouse.external_order_id
Shopify order.line_items → Warehouse.fulfillment_items
Shopify order.shipping_address → Warehouse.destination

IDEMPOTENCY: Use Shopify order ID as a unique key in the warehouse system to prevent duplicate fulfillment records if the webhook fires more than once (Shopify webhooks are at-least-once delivery).

FAILURE HANDLING: If warehouse system is unavailable, queue the webhook payload and retry with exponential backoff (e.g. 1min, 5min, 30min); alert on 3 consecutive failures.

RATE LIMITS: Shopify Admin API allows 2 requests/second on standard plans — batch or queue if processing volume could spike during sales events.

FAQ

What is this skill for?
It turns a description of two systems needing integration into a complete technical spec covering auth, data flow, and failure handling.
How do I install it?
Upload the SKILL.md file to a Claude conversation and describe the two systems and desired data flow.
Does it write the actual integration code?
No, it produces the technical spec/plan; use it to scope the work before implementation, or pair with a coding tool to build from the spec.
Does it know the actual API details of specific platforms like Shopify or Salesforce?
It uses general knowledge of common platform patterns (webhooks, rate limits, auth methods); always verify exact current API details against official documentation before implementing.
How is this different from just listing what data needs to move?
It forces consideration of authentication, idempotency, failure/retry handling, and rate limits — the parts of an integration that most commonly cause production bugs if skipped.
Can it spec integrations between two custom internal systems, not just known platforms?
Yes, describe both systems generically and the spec will use general best-practice patterns rather than platform-specific details.

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