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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuine value by describing the return payload (quote text, speaker, X handle, timestamp, surrounding lines, episode link), which matters since there is no output schema. It omits pagination/limit behavior.

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?

Three short sentences, each load-bearing: scope first, return payload second, best-use case third. No filler or repetition of the title.

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?

Purpose and return shape are adequately covered without an output schema, and annotations handle safety. However, the description never explains the date-range or speaker filters, so an agent cannot confidently use the tool's filtering capability from the description alone.

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 description coverage is only 20%: only query is documented in-schema, and the description adds nothing about from/to date bounds, the speaker filter, or the limit cap of 20. With four of five parameters undocumented, the description fails to compensate for the coverage gap.

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 verb and resource ('exact-word search across every ATC transcript line') and adds the intended use case ('who said X' and quotes). It does not explicitly distinguish itself from siblings like search or search_segments, so an agent must infer the boundary from the 'exact words' vs. semantic framing.

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?

'Best for who said X and quotes' gives an implied usage context, but there is no explicit when-not-to-use and no named alternative (search_segments, search). The agent must guess that broader/topical queries belong elsewhere.

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