Agent skill · software engineering · jeremylongshore
processing-api-batches
Optimize bulk API requests with batching, throttling, and parallel execution.
Why this skill is useful
Adds multiple executable scripts for batch processing with concurrency control and error handling that aren't in public docs.
What it needs
Requires bull, bullmq, redis installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Processing API Batches Overview Optimize bulk API operations with batch request endpoints, parallel execution with concurrency control, partial failure handling, and progress tracking. Implement batch processing patterns that accept arrays of operations in a single request, execute them efficiently with database bulk operations, and return per-item results with individual success/failure status. Prerequisites Web framework capable of handling large request bodies (configure body size limits: 10MB+ for batch payloads) Database with bulk operation support (bulk insert, bulk update, transactions) Queue system for async batch processing: Bull/BullMQ (Node.js), Celery (Python), or SQS Progress tracking store (Redis) for long-running batch status polling Rate limiting aware of batch operations (count individual operations, not just requests) Instructions 1. Examine existing API endpoints using Read and Grep to identify operations frequently called in loops by consumers, which are candidates for batch equivalents. 2. Design the batch request format: accept an array of operations in the request body, each with an optional client-provided id for result correlation, e.g., POST /batch with {operations: [{method: "POST", path: "/users", body: {...}, id: "op1"}]}. 3. Implement synchronous batch processing for small batches (< 100 items): validate all items, execute in a database transaction, and return per-item results with {id, status, result error} for each operation. 4. Add asynchronous batch processing for large batches (> 100 items): accept the batch, return 202 Accepted with a batchId and status polling URL, process in a background worker, and update progress in Redis. 5. Implement concurrency control: process batch items in parallel with configurable concurrency limit (default: 10) using p-limit or asyncio.Semaphore to prevent database connection exhaustion. 6. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/processing-api-batches--53bdd0