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

Annotations already declare readOnlyHint=true, openWorldHint=false, and idempotentHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond that: the data comes from stored results, the lookback windows differ by kind (14/30 days for jockey/trainer, 365 days for course), and exactly what each kind returns. It does not mention rate limits or latency, which keeps it short of 5.

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 sentences with no filler, and the data-source framing is front-loaded ahead of the per-kind detail. The 'kind jockey or trainer...' phrasing is telegraphic but still parseable and compact for the amount of information conveyed.

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?

There is no output schema, so the description carries the return-value burden and does so thoroughly, enumerating the metrics produced for each kind including sample sizes for the draw bands. It is essentially complete for a two-parameter stats lookup; only cross-tool routing and pagination/limits are absent.

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 100%, so the baseline is 3. The description goes beyond the schema by unpacking what each kind value actually yields (runs/wins/places/strike rate vs favourite win rate, top jockeys/trainers, draw bands), giving the agent semantic depth the bare enum-like schema lacks.

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 description states a specific resource (racing stats) and precisely enumerates the metrics returned for each kind value, so an agent knows exactly what it gets. It does not name a competing sibling tool, but no sibling in the list appears to overlap with racing stats, so differentiation is implicit rather than explicit.

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 two kind modes are described well enough that an agent can infer which to use for a jockey/trainer versus a course, but there is no explicit when-to-use guidance, no prerequisites, and no routing to alternatives such as find_race or find_horses. Usage is implied through the kind breakdown only.

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