clade-prod-checklist

Production readiness checklist for Claude-powered applications — Use when working with prod-checklist patterns. error handling, monitoring, fallbacks, cost controls, and security. Trigger with "anthropic production", "claude production ready", "anthropic launch checklist", "go live with claude".

25 stars

Best use case

clade-prod-checklist is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Production readiness checklist for Claude-powered applications — Use when working with prod-checklist patterns. error handling, monitoring, fallbacks, cost controls, and security. Trigger with "anthropic production", "claude production ready", "anthropic launch checklist", "go live with claude".

Teams using clade-prod-checklist should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/clade-prod-checklist/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/jeremylongshore/claude-code-plugins-plus-skills/clade-prod-checklist/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/clade-prod-checklist/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How clade-prod-checklist Compares

Feature / Agentclade-prod-checklistStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Production readiness checklist for Claude-powered applications — Use when working with prod-checklist patterns. error handling, monitoring, fallbacks, cost controls, and security. Trigger with "anthropic production", "claude production ready", "anthropic launch checklist", "go live with claude".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Anthropic Production Checklist

## Overview
Before going live with a Claude-powered app, verify every item below.

## Authentication & Security
- [ ] API key stored in secrets manager (not in code or env file on disk)
- [ ] Key rotated — not the same one used during development
- [ ] Server-side only — no key exposed to client/browser
- [ ] Per-user rate limiting in place
- [ ] Input validation: max length, content filtering
- [ ] System prompt includes injection guardrails

## Output
- All checklist items verified (authentication, error handling, streaming, cost, monitoring, reliability, content, performance)
- Production API key configured with appropriate spending limits
- Monitoring and alerting in place
- Fallback behavior tested for API outages

## Error Handling
- [ ] All Anthropic API calls wrapped in try/catch
- [ ] `RateLimitError` (429) → backoff and retry
- [ ] `OverloadedError` (529) → fallback model or queue
- [ ] `AuthenticationError` (401) → alert team, don't retry
- [ ] `InvalidRequestError` (400) → log and fix, don't retry
- [ ] Network errors → retry with backoff
- [ ] Request IDs logged for every error (for support tickets)

## Streaming
- [ ] Using `client.messages.stream()` for user-facing responses
- [ ] Stream errors handled (connection drops, incomplete responses)
- [ ] `stop_reason` checked: `end_turn` vs `max_tokens` (incomplete)

## Cost Controls
- [ ] `max_tokens` set to realistic values (not 4096 for short answers)
- [ ] Correct model for each task (Haiku for simple, Sonnet for balanced)
- [ ] Prompt caching enabled for repeated system prompts
- [ ] Usage logging in place — tracking tokens and cost per request
- [ ] Spending alerts set in Anthropic console

## Monitoring
- [ ] Response latency tracked (TTFT and total)
- [ ] Token usage tracked (input/output per request)
- [ ] Error rates dashboarded (by error type)
- [ ] Anthropic status page monitored ([status.anthropic.com](https://status.anthropic.com))

## Reliability
- [ ] SDK `maxRetries` set (default 2 is fine for most)
- [ ] Timeout configured for your use case (`timeout` option)
- [ ] Single client instance reused (not created per request)
- [ ] Graceful degradation if Claude is down (cached responses, fallback)

## Content & Compliance
- [ ] System prompt tested against edge cases and adversarial inputs
- [ ] Output validated before showing to users (JSON parsing, length)
- [ ] Data retention settings configured in Anthropic console
- [ ] No unnecessary PII in prompts
- [ ] Usage policy compliance (Anthropic's Acceptable Use Policy)

## Performance
- [ ] p95 latency acceptable for your UX
- [ ] Prompt caching for latency-sensitive paths
- [ ] Parallel requests where possible (`Promise.all`)
- [ ] Client-side streaming UI implemented

## Examples
Each section above is a verifiable checklist. Work through Authentication & Security, Error Handling, Streaming, Cost Controls, Monitoring, Reliability, Content & Compliance, and Performance sections.

## Resources
- [API Best Practices](https://docs.anthropic.com/en/docs/build-with-claude)
- [Error Handling](https://docs.anthropic.com/en/api/errors)
- [Rate Limits](https://docs.anthropic.com/en/api/rate-limits)
- [Acceptable Use Policy](https://www.anthropic.com/policies/aup)

## Next Steps
See `clade-observability` for monitoring setup.

## Prerequisites
- All other anthropic skills reviewed
- Application feature-complete and tested locally
- Production API key created (separate from dev)
- Deployment platform selected

## Instructions

### Step 1: Review the patterns below
Each section contains production-ready code examples. Copy and adapt them to your use case.

### Step 2: Apply to your codebase
Integrate the patterns that match your requirements. Test each change individually.

### Step 3: Verify
Run your test suite to confirm the integration works correctly.

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