Anthropic Advanced Troubleshooting

Issue: Context Window Overflow

# Symptom: invalid_request_error about token count
# Diagnosis: pre-check with Token Counting API
import anthropic

client = anthropic.Anthropic()

count = client.messages.count_tokens(
    model="claude-sonnet-4-20250514",
    messages=conversation_history,
    system=system_prompt
)
print(f"Input tokens: {count.input_tokens}")
# Claude Sonnet: 200K context, Claude Opus: 200K context

# Fix: truncate oldest messages or summarize
def trim_conversation(messages: list, max_tokens: int = 180_000) -> list:
    """Keep recent messages within token budget."""
    # Always keep first (system context) and last 5 messages
    if len(messages) <= 5:
        return messages
    return messages[:1] + messages[-5:]  # Crude but effective

Issue: Tool Use Not Triggering

# Symptom: Claude responds with text instead of calling tools
# Diagnosis checklist:
# 1. Tool description must clearly state WHEN to use the tool
# 2. User message must match the tool's trigger condition

# BAD description (too vague):
{"name": "search", "description": "Search for things"}

# GOOD description (clear trigger):
{"name": "search_products", "description": "Search the product catalog by name, category, or price range. Use whenever the user asks about products, pricing, or availability."}

# Force tool use if needed:
message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    tools=tools,
    tool_choice={"type": "any"},  # Must call at least one tool
    messages=[{"role": "user", "content": "Find products under $50"}]
)

Issue: Streaming Drops or Corruption

# Symptom: stream ends prematurely or text is garbled
# Cause: network interruption, proxy timeout, or large response

# Fix: implement reconnection with content tracking
def resilient_stream(client, **kwargs):
    """Stream with reconnection on failure."""
    collected_text = ""
    max_retries = 3

    for attempt in range(max_retries):
        try:
            with client.messages.stream(**kwargs) as stream:
                for text in stream.text_stream:
                    collected_text += text
                    yield text
                return  # Success
        except Exception as e:
            if attempt == max_retries - 1:
                raise
            # Note: Claude streams are NOT resumable
            # Must restart from beginning
            collected_text = ""
            print(f"Stream interrupted, retrying ({attempt + 1}/{max_retries})")

Issue: Unexpected Stop Reason

# Debug unexpected truncation
msg = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=4096,  # Was it too low?
    messages=[{"role": "user", "content": long_prompt}]
)
print(f"Stop reason: {msg.stop_reason}")
print(f"Output tokens: {msg.usage.output_tokens}")
print(f"Max tokens: 4096")
# If output_tokens == max_tokens, response was truncated

Issue: Response Quality Degradation

# Checklist for quality issues:
# 1. System prompt too long or contradictory?
# 2. Conversation history too noisy (too many turns)?
# 3. Wrong model for task complexity?
# 4. Temperature too high for deterministic tasks?

# Debug: log the full request for review
import json
request_params = {
    "model": model,
    "max_tokens": max_tokens,
    "system": system[:200] + "...",  # Truncated for logging
    "message_count": len(messages),
    "temperature": temperature,
}
print(f"Request config: {json.dumps(request_params, indent=2)}")

Diagnostic Curl Commands

# Test specific model availability
for model in claude-haiku-4-20250514 claude-sonnet-4-20250514 claude-opus-4-20250514; do
  echo -n "$model: "
  curl -s -o /dev/null -w "%{http_code}" https://api.anthropic.com/v1/messages \
    -H "x-api-key: $ANTHROPIC_API_KEY" \
    -H "anthropic-version: 2023-06-01" \
    -H "content-type: application/json" \
    -d "{\"model\":\"$model\",\"max_tokens\":8,\"messages\":[{\"role\":\"user\",\"content\":\"hi\"}]}"
  echo
done

Resources

• Error Reference
• Token Counting
• Tool Use Guide

Next Steps

For load testing, see anth-load-scale.