or run

tessl search

idempotency-handling

tessl install https://github.com/secondsky/claude-skills --skill idempotency-handling

github.com/secondsky/claude-skills

Idempotent API operations with idempotency keys, Redis caching, DB constraints. Use for payment systems, webhook retries, safe retries, or encountering duplicate processing, race conditions, key expiry errors.

Average Score

94%

Content

92%

Description

100%

SKILL.md

Review

Evals

Idempotency Handling

Ensure operations produce identical results regardless of execution count.

Idempotency Key Pattern

const redis = require('redis');
const client = redis.createClient();

async function idempotencyMiddleware(req, res, next) {
  const key = req.headers['idempotency-key'];
  if (!key) return next();

  const cached = await client.get(`idempotency:${key}`);
  if (cached) {
    const { status, body } = JSON.parse(cached);
    return res.status(status).json(body);
  }

  // Store original send
  const originalSend = res.json.bind(res);
  res.json = async (body) => {
    await client.setEx(
      `idempotency:${key}`,
      86400, // 24 hours
      JSON.stringify({ status: res.statusCode, body })
    );
    return originalSend(body);
  };

  next();
}

Database-Backed Idempotency

CREATE TABLE idempotency_keys (
  key VARCHAR(255) PRIMARY KEY,
  request_hash VARCHAR(64) NOT NULL,
  response JSONB,
  status VARCHAR(20) DEFAULT 'processing',
  created_at TIMESTAMP DEFAULT NOW(),
  expires_at TIMESTAMP DEFAULT NOW() + INTERVAL '24 hours'
);

CREATE INDEX idx_idempotency_expires ON idempotency_keys(expires_at);

async function processPayment(idempotencyKey, payload) {
  const requestHash = crypto.createHash('sha256')
    .update(JSON.stringify(payload)).digest('hex');

  // Try to insert with 'processing' status - only one request will succeed
  const insertResult = await db.query(
    `INSERT INTO idempotency_keys (key, request_hash, status)
     VALUES ($1, $2, 'processing')
     ON CONFLICT (key) DO NOTHING
     RETURNING *`,
    [idempotencyKey, requestHash]
  );

  // If we inserted the row (rowCount === 1), we're responsible for processing
  if (insertResult.rowCount === 1) {
    try {
      // Execute the payment
      const result = await executePayment(payload);

      // Update to completed with response
      await db.query(
        'UPDATE idempotency_keys SET status = $1, response = $2 WHERE key = $3',
        ['completed', JSON.stringify(result), idempotencyKey]
      );

      return result;
    } catch (error) {
      // Mark as failed on error
      await db.query(
        'UPDATE idempotency_keys SET status = $1, response = $2 WHERE key = $3',
        ['failed', JSON.stringify({ error: error.message }), idempotencyKey]
      );
      throw error;
    }
  }

  // Another request is/was processing this key - check status
  const existing = await db.query(
    'SELECT * FROM idempotency_keys WHERE key = $1',
    [idempotencyKey]
  );

  const row = existing.rows[0];
  if (!row) {
    throw new Error('Unexpected: idempotency key vanished');
  }

  // Verify request hasn't changed
  if (row.request_hash !== requestHash) {
    throw new Error('Idempotency key reused with different request');
  }

  // Check status
  if (row.status === 'completed') {
    return JSON.parse(row.response);
  } else if (row.status === 'processing') {
    throw new Error('Request already processing - retry later');
  } else if (row.status === 'failed') {
    const failedResponse = JSON.parse(row.response);
    throw new Error(`Previous attempt failed: ${failedResponse.error}`);
  }

  throw new Error(`Unknown status: ${row.status}`);
}

When to Apply

Payment processing
Order creation
Webhook handling
Email sending
Any operation where duplicates cause issues

Best Practices

Require idempotency keys for mutations
Validate request body matches stored request
Set appropriate TTL (24 hours typical)
Use atomic database operations
Implement cleanup jobs to prevent table bloat

TTL Cleanup Strategy

To prevent unbounded table growth, implement periodic cleanup of expired keys:

Option 1: Scheduled Database Job (PostgreSQL)

-- Run hourly via pg_cron or external scheduler
DELETE FROM idempotency_keys
WHERE expires_at < NOW()
LIMIT 1000; -- Batch delete to avoid long locks

Option 2: Application Cleanup Job (Node.js)

// Run via cron or job scheduler (e.g., node-cron, Bull)
async function cleanupExpiredKeys() {
  try {
    const result = await db.query(
      'DELETE FROM idempotency_keys WHERE expires_at < NOW()'
    );
    console.log(`Cleaned up ${result.rowCount} expired idempotency keys`);
  } catch (error) {
    console.error('Cleanup job failed:', error);
  }
}

// Schedule to run every hour
cron.schedule('0 * * * *', cleanupExpiredKeys);

Option 3: Application Cleanup Job (Python)

import asyncio
from datetime import datetime

async def cleanup_expired_keys():
    """Remove expired idempotency keys to prevent table bloat."""
    try:
        result = await db.execute(
            "DELETE FROM idempotency_keys WHERE expires_at < $1",
            datetime.now()
        )
        print(f"Cleaned up {result} expired idempotency keys")
    except Exception as e:
        print(f"Cleanup job failed: {e}")

# Run with APScheduler, Celery, or similar
# scheduler.add_job(cleanup_expired_keys, 'interval', hours=1)

Cleanup Best Practices:

Run cleanup during low-traffic periods to minimize lock contention
Use batched deletes (LIMIT 1000) for large tables
Monitor cleanup job execution and failures
Consider partitioning the table by created_at for easier cleanup
Set up alerts if table size grows unexpectedly