detect_hallucinations

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It discloses the return shape and enumerates the detectors, which is useful. However, it does not state whether this operation mutates anything, requires prior transcription, or has any side effects or performance implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences, with the main action and output in the first sentence and an exhaustive but relevant detector list in the second. Every part earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, the description explains both input context and output fields. It does not elaborate on what 'TranscriptResult' is or what each detector checks, but the sibling tool transcribe and the detector names supply enough context for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%: the single parameter is already described as 'JSON string of a TranscriptResult'. The description adds no further parameter-level detail, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific action ('Run all hallucination detectors') on a specific resource ('a transcript') and clearly describes the output (flags with severity, detector name, evidence). The detector list differentiates it from siblings like transcribe, repair, score, and estimate_cost.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Run all hallucination detectors on a transcript' makes the intended use case clear: after transcription, when hallucination detection is needed. It does not explicitly name alternatives or exclusions, but the sibling names make the context obvious enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.