Over-Helpfulness

Problem

An agent that always answers will answer even when it should not. When a request needs a tool the agent lacks, a fact it cannot verify, or an action outside its mandate, the helpful default is to attempt it anyway and present the result as if it were reliable. The failure is silent: there is no abstention signal, the output looks like every correct output, and the cost lands downstream when someone acts on a fabricated answer or an out-of-scope action. The agent never weighs whether the task is one it is fit to complete.

Solution

Recognise the smell first: the agent produces a fluent, confident answer for requests it has no means to satisfy, never returns a calibrated 'I cannot do this', and its error rate climbs sharply on out-of-scope inputs while its expressed confidence does not. To remove it, place a gate before the answer that compares the request against the agent's declared tools, knowledge boundary, and policy, and route requests that fail the gate to abstention, a clarifying question, or a handoff to a capable agent or a human. Make abstaining a first-class, rewarded outcome rather than a hidden failure, and surface a machine-readable reason so callers can route on it. The named cures in the catalog are an explicit self-model, scoped refusal, and typed refusal codes.

When to use

• An agent answers fluently for requests it has no tool, no verified knowledge, or no mandate to satisfy.
• Error rate climbs on out-of-scope inputs while expressed confidence stays flat, and there is no abstention path.
• Reviewing why downstream failures trace back to an agent acting past its declared capability.