Anthropic Known Pitfalls

Overview

Ten common mistakes when building with the Anthropic API and how to avoid them: forgetting max_tokens (required), system prompt in messages array (wrong), non-alternating messages, unchecked stop_reason, creating client per request, no 529 handling, hardcoded model IDs, expensive output tokens, no streaming, and unnecessary PII.

1. Forgetting max_tokens

Unlike OpenAI, max_tokens is required. Omitting it returns a 400 error.

// BAD
await client.messages.create({ model: 'claude-sonnet-4-20250514', messages });

// GOOD
await client.messages.create({ model: 'claude-sonnet-4-20250514', max_tokens: 1024, messages });

2. System Prompt in Messages Array

Claude uses a top-level system parameter, not a system message in the array.

// BAD — this sends "system" as a user message role, which will error
messages: [{ role: 'system', content: '...' }, { role: 'user', content: '...' }]

// GOOD
system: 'You are helpful.',
messages: [{ role: 'user', content: '...' }]

3. Non-Alternating Messages

Messages must strictly alternate between user and assistant.

// BAD — two user messages in a row
messages: [
  { role: 'user', content: 'Hello' },
  { role: 'user', content: 'How are you?' }, // ERROR
]

// GOOD — combine into one or add assistant between
messages: [
  { role: 'user', content: 'Hello. How are you?' },
]

4. Not Checking stop_reason

If stop_reason === 'max_tokens', the response was truncated.

if (message.stop_reason === 'max_tokens') {
  // Response is incomplete — increase max_tokens or handle truncation
}

5. Creating Client Per Request

Each new Anthropic() creates a new connection pool. In serverless, this adds latency.