Anth prod checklist
Skill ComeOnOliver/skillshub/skills/jeremylongshore/claude-code-plugins-plus-skills/anth-prod-checklist
Execute production deployment checklist for Claude API integrations. Use when deploying Claude-powered features to production, preparing for launch, or implementing go-live validation. Trigger with phrases like "anthropic production", "deploy claude", "claude go-live", "anthropic launch checklist", "production ready claude".From its SKILL.md
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SKILL.md
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Anthropic Production Checklist
Overview
Complete checklist for deploying Claude API integrations to production with reliability, observability, and cost controls.
Pre-Launch Checklist
Authentication & Keys
- Production API key from dedicated Workspace
- Key stored in secret manager (not env files on servers)
- Key rotation procedure documented and tested
- Separate keys for each environment (dev/staging/prod)
Error Handling
- All 5 error types handled:
authentication_error,invalid_request_error,rate_limit_error,api_error,overloaded_error - SDK
maxRetriesset (recommended: 3-5 for production) - Custom error logging with
request-idcaptured - Circuit breaker for sustained API failures
Rate Limits & Cost
- Usage tier verified at console.anthropic.com
- Application-level rate limiting implemented
- Cost alerts configured (monthly spend caps)
- Model selection optimized (Haiku for simple tasks, Sonnet for complex)
-
max_tokensset to realistic values (not inflated) - Prompt caching enabled for repeated system prompts
Reliability
- Timeout configured (
timeoutparameter, recommended 60-120s) - Graceful degradation when API is unavailable
- Health check endpoint tests API connectivity
async def health_check():
try:
# Use token counting as a cheap health probe (no generation cost)
count = client.messages.count_tokens(
model="claude-haiku-4-20250514",
messages=[{"role": "user", "content": "ping"}]
)
return {"status": "healthy", "tokens": count.input_tokens}
except Exception as e:
return {"status": "degraded", "error": str(e)}
Observability
- Request/response logging (redact content, keep metadata)
- Latency tracking (p50, p95, p99)
- Token usage tracking (input + output per request)
- Cost tracking per feature/customer
- Error rate alerting (429s, 5xx, timeouts)
import logging
import time
logger = logging.getLogger("anthropic")
def tracked_create(**kwargs):
start = time.monotonic()
try:
response = client.messages.create(**kwargs)
duration = time.monotonic() - start
logger.info(
"claude_request",
extra={
"request_id": response._request_id,
"model": response.model,
"input_tokens": response.usage.input_tokens,
"output_tokens": response.usage.output_tokens,
"duration_ms": int(duration * 1000),
"stop_reason": response.stop_reason,
}
)
return response
except Exception as e:
duration = time.monotonic() - start
logger.error("claude_error", extra={"error": str(e), "duration_ms": int(duration * 1000)})
raise
Content Safety
- System prompts reviewed for injection resistance
- User input validated and length-limited
- Output scanned for sensitive data leakage
- Content moderation for user-facing responses
Infrastructure
- Deployment uses canary/rolling strategy
- Rollback procedure documented and tested
- Runbook created (see
anth-incident-runbook) - On-call escalation path defined
Alerting Thresholds
| Metric | Warning | Critical |
|---|---|---|
| Error rate (5xx) | > 1% | > 5% |
| p99 latency | > 10s | > 30s |
| 429 rate | > 5/min | > 20/min |
| Daily cost | > 80% budget | > 100% budget |
| Auth failures (401/403) | > 0 | > 0 (immediate) |
Resources
Next Steps
For version upgrades, see anth-upgrade-migration.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.