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

Annotations already establish read-only, idempotent, closed-world behavior, and the description adds real value beyond them: it lists what each result contains (question, headline, answers, figures, cohort, measurement date) and notes it requires no Desk Pass, which matters because get_desk_pass exists as a sibling. It doesn't discuss result volume or limits on returned pieces beyond what the schema already states.

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?

Sentences are front-loaded and each carries distinct information: purpose, return contents, when-to-use, when-not, parameters, and access requirement. Slightly longer than strictly necessary, but there is no filler or repetition.

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?

With no output schema, the description compensates by describing the shape of each returned piece and the cohort/measurement-date metadata. Combined with the when-not rule and the authentication note, an agent has everything needed to call this correctly.

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%, so the baseline is 3. The description reinforces intended values for `about` ('a few words on the question') and `pieces`, but never mentions the third parameter `asked`, leaving the verbatim-question convention to the schema alone.

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?

The first sentence names a specific verb and resource (reads the Desk's published research) and narrows scope to players 'in general, word for word.' The later exclusion of 'one named player, team or match' implicitly separates it from query_player_history and query_team_record, though no sibling is named outright.

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?

It gives an explicit use case ('when someone asks about players or teams in general, such as how often players move up or back down, or home advantage') and an explicit never-condition ('never call it for one named player, team or match'). It stops short of pointing to the specific alternative tool for those per-entity questions.

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