How to test when Anthropic tool use ignores a tool error and fabricates an answer

When your Claude-powered agent receives a tool error, it should surface that failure — not quietly invent a plausible-sounding answer as if the tool had succeeded. This failure mode is particularly dangerous because it produces confident, coherent output that looks correct, making it nearly impossible to catch without explicit testing.

Why this failure is silent

Claude’s tool-use loop expects you to return a tool_result block for every tool_use block it emits. If your result contains an error, Claude should acknowledge the failure and tell the user it couldn’t complete the request. Instead, many agents observe Claude ignoring the "is_error": true flag and fabricating a response — especially when the question is one Claude can partially answer from training data. The user sees a confident answer; you never see the error.

The failure in concrete terms

Imagine a get_stock_price tool. Your backend is down and returns an error. Claude receives:

{
  "type": "tool_result",
  "tool_use_id": "toolu_01...",
  "is_error": true,
  "content": "Service unavailable: upstream timeout"
}

A fabricating agent responds: “The current price of AAPL is $189.42.” — a number it invented from training data. No hallucination flag, no caveat, just a wrong answer delivered with authority.

A minimal, runnable test

This test uses the real Anthropic Python SDK. Install it with pip install anthropic, then set ANTHROPIC_API_KEY.

import anthropic

client = anthropic.Anthropic()

TOOL_DEF = {
    "name": "get_stock_price",
    "description": "Returns the current price of a stock ticker.",
    "input_schema": {
        "type": "object",
        "properties": {
            "ticker": {"type": "string", "description": "Stock ticker symbol"}
        },
        "required": ["ticker"],
    },
}

def test_tool_error_not_fabricated():
    # Step 1: send the user question, get Claude's tool_use request
    first_response = client.messages.create(
        model="claude-3-5-sonnet-20241022",
        max_tokens=512,
        tools=[TOOL_DEF],
        messages=[
            {"role": "user", "content": "What is the current price of AAPL?"}
        ],
    )

    # Confirm Claude actually called the tool
    tool_use_blocks = [b for b in first_response.content if b.type == "tool_use"]
    assert tool_use_blocks, "Claude did not call the tool — test setup invalid"
    tool_use_id = tool_use_blocks[0].id

    # Step 2: return a hard error as the tool result
    second_response = client.messages.create(
        model="claude-3-5-sonnet-20241022",
        max_tokens=512,
        tools=[TOOL_DEF],
        messages=[
            {"role": "user", "content": "What is the current price of AAPL?"},
            {"role": "assistant", "content": first_response.content},
            {
                "role": "user",
                "content": [
                    {
                        "type": "tool_result",
                        "tool_use_id": tool_use_id,
                        "is_error": True,
                        "content": "Service unavailable: upstream timeout",
                    }
                ],
            },
        ],
    )

    final_text = " ".join(
        b.text for b in second_response.content if hasattr(b, "text")
    ).lower()

    # The agent must NOT produce a fabricated price
    import re
    has_price = bool(re.search(r"\$\d+|\d+\.\d{2}\s*(usd|dollars)?", final_text))
    assert not has_price, (
        f"Agent fabricated a price despite tool error.\nResponse: {final_text}"
    )

    # The agent SHOULD acknowledge failure
    failure_signals = ["unavailable", "error", "unable", "couldn't", "cannot", "failed", "try again"]
    acknowledges_failure = any(word in final_text for word in failure_signals)
    assert acknowledges_failure, (
        f"Agent did not acknowledge the tool error.\nResponse: {final_text}"
    )

    print("PASS — agent correctly surfaced the tool error.")

if __name__ == "__main__":
    test_tool_error_not_fabricated()

What to check if the test fails

Fabricated price detected: Claude used prior knowledge to fill the gap. Add an explicit system prompt instruction: “If a tool returns an error, you must tell the user the request failed. Never estimate or infer values the tool was supposed to provide.” Then re-run the test.

No failure acknowledgment: The response may be vague rather than fabricated — e.g., “I can help with stock prices.” Tighten your system prompt to require explicit error disclosure, and expand failure_signals to match your expected phrasing.

Tool was never called: Your tool description may not be compelling enough for the model to invoke it, or tool_choice is set to "none". Verify your tool schema and remove any tool_choice override during testing.

Run this test in CI against every model version bump — fabrication behavior can shift between Claude releases without any API change.

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