Silent API failures mislead AI agents into trusting wrong results
A developer found that a popular email API returned HTTP 200 with unfiltered results when asked for bounced emails, which an AI agent could present to users as accurate. A study of 27 live vendor APIs using 219 deliberately wrong requests found that constraints stated only in documentation, rather than enforced in schemas, led to silent failures that agents rarely noticed or corrected. Agents frequently gave users false information, sometimes claiming items did not exist or inventing figures. Other examples include an AI agent community platform where filters were ignored without error and an API that dropped unknown fields without warning. The author also points to a response that violated its own spec when a field-selection option was used and to confusing use of 400 and 401 status codes. The findings suggest that machine-checkable constraints and honest error responses are essential for reliable agent behavior.
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