Why Use This
This skill provides specialized capabilities for jeremylongshore's codebase.
Use Cases
- Developing new features in the jeremylongshore repository
- Refactoring existing code to follow jeremylongshore standards
- Understanding and working with jeremylongshore's codebase structure
Install Guide
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https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/main/plugins/saas-packs/exa-pack/skills/exa-prod-checklist
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Updated At May 23, 2026, 05:41 AM
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SKILL.md 182 Lines
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License MIT
---
name: exa-prod-checklist
description: 'Execute Exa production deployment checklist with pre-flight, deploy,
and rollback.
Use when deploying Exa integrations to production, preparing for launch,
or verifying production readiness.
Trigger with phrases like "exa production", "deploy exa to prod",
"exa go-live", "exa launch checklist", "exa production ready".
'
allowed-tools: Read, Bash(curl:*), Bash(node:*), Grep
version: 1.0.0
license: MIT
author: Jeremy Longshore <[email protected]>
tags:
- saas
- exa
- deployment
- production
compatibility: Designed for Claude Code, also compatible with Codex and OpenClaw
---
# Exa Production Checklist
## Overview
Complete checklist for deploying Exa search integrations to production. Covers API key management, error handling verification, performance baselines, monitoring, and rollback procedures.
## Pre-Deployment Checklist
### Security
- [ ] Production API key stored in secret manager (not env file)
- [ ] Different API keys for dev/staging/production
- [ ] `.env` files in `.gitignore`
- [ ] Git history scanned for accidentally committed keys
- [ ] API key has minimal scopes needed
### Code Quality
- [ ] All tests passing (unit + integration)
- [ ] No hardcoded API keys or URLs
- [ ] Error handling covers all Exa HTTP codes (400, 401, 402, 403, 429, 5xx)
- [ ] `requestId` captured from error responses
- [ ] Rate limiting/exponential backoff implemented
- [ ] Content moderation enabled (`moderation: true`) for user-facing search
### Performance
- [ ] Search type appropriate for latency SLO (`fast`/`auto`/`neural`)
- [ ] `numResults` minimized per use case (3-5 for most)
- [ ] `maxCharacters` set on text and highlights
- [ ] Result caching enabled (LRU or Redis)
- [ ] Request queue with concurrency limit (respect 10 QPS default)
### Monitoring
- [ ] Search latency histogram instrumented
- [ ] Error rate counter by status code
- [ ] Cache hit/miss rate tracked
- [ ] Daily search volume tracked (for budget)
- [ ] Alerts configured for latency > 3s, error rate > 5%
## Deploy Procedure
### Step 1: Pre-Flight Verification
```bash
set -euo pipefail
echo "=== Exa Pre-Flight ==="
# 1. Verify production API key works
HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" \
-X POST https://api.exa.ai/search \
-H "x-api-key: $EXA_API_KEY_PROD" \
-H "Content-Type: application/json" \
-d '{"query":"pre-flight check","numResults":1}')
echo "API Status: $HTTP_CODE"
[ "$HTTP_CODE" = "200" ] || { echo "FAIL: API key invalid"; exit 1; }
# 2. Verify tests pass
npm test || { echo "FAIL: Tests failing"; exit 1; }
echo "Pre-flight PASSED"
```
### Step 2: Health Check Endpoint
```typescript
import Exa from "exa-js";
const exa = new Exa(process.env.EXA_API_KEY);
app.get("/health/exa", async (_req, res) => {
const start = performance.now();
try {
const result = await exa.search("health check", { numResults: 1 });
const latencyMs = Math.round(performance.now() - start);
res.json({
status: "healthy",
latencyMs,
resultCount: result.results.length,
timestamp: new Date().toISOString(),
});
} catch (err: any) {
res.status(503).json({
status: "unhealthy",
error: err.message,
errorCode: err.status,
latencyMs: Math.round(performance.now() - start),
});
}
});
```
### Step 3: Gradual Rollout
```bash
set -euo pipefail
# Deploy canary (10% traffic)
kubectl apply -f k8s/production.yaml
kubectl rollout pause deployment/exa-service
echo "Canary deployed. Monitor for 10 minutes..."
echo "Check: /health/exa endpoint, error rates, latency"
# After monitoring, resume to full rollout
# kubectl rollout resume deployment/exa-service
```
## Post-Deployment Verification
```bash
set -euo pipefail
# Verify production endpoint
curl -sf https://your-app.com/health/exa | python3 -m json.tool
# Check error rates (if Prometheus available)
curl -s "localhost:9090/api/v1/query?query=rate(exa_search_error[5m])" 2>/dev/null
```
## Rollback Procedure
```bash
set -euo pipefail
# Immediate rollback
kubectl rollout undo deployment/exa-service
kubectl rollout status deployment/exa-service
echo "Rollback complete. Verify /health/exa endpoint."
```
## Alert Thresholds
| Alert | Condition | Severity |
|-------|-----------|----------|
| API Down | 5xx errors > 10/min | P1 |
| Auth Failure | 401/403 errors > 0 | P1 |
| Rate Limited | 429 errors > 5/min | P2 |
| High Latency | P95 > 5000ms | P2 |
| Budget Warning | Daily searches > 80% of limit | P3 |
## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Health check fails | API key not set in prod | Verify secret injection |
| Latency spike after deploy | Missing cache warm-up | Pre-populate cache |
| Rate limit on launch | Traffic spike | Enable request queue |
| Rollback needed | Error rate spike | `kubectl rollout undo` |
## Resources
- [Exa API Documentation](https://docs.exa.ai)
- [Exa Error Codes](https://docs.exa.ai/reference/error-codes)
## Next Steps
For version upgrades, see `exa-upgrade-migration`. For incident response, see `exa-incident-runbook`.