fund_leaderboard

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds meaningful behavior beyond those: the 13F public-date timing, 30/60/90-day measurement windows, the meaning of `window`, and the `measured: false` outcome for funds without enough history. This is substantial behavioral context that an agent cannot infer from annotations or the empty input schema.

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?

The description is compact and front-loaded: the core purpose is in the first sentence, followed by the most important measurement nuance and a pointer to the sibling detail tool. Every sentence adds distinct value, and the structure moves from high-level purpose to operational detail without 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?

Given zero parameters, an existing output schema, and read-only/idempotent annotations, the description covers everything an agent needs to decide whether to call this tool. It explains the ranking methodology, data timing, eligibility caveats, and where to get more detail, making the definition self-sufficient for correct invocation.

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?

The input schema has zero parameters, so the baseline is 4 because there are no parameter semantics to document. The description goes further by defining `window` as the longest horizon with data, which likely corresponds to an output concept and helps interpret results. There is no missing parameter documentation to penalize.

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 opens with a precise statement: 'Institutional investors (13F filers) ranked by how their position changes performed vs SPY.' This names the subject, the action, and the comparison benchmark, making it clearly distinguishable from siblings like leaderboard or fund_track_record. It also immediately clarifies what the tool measures rather than just restating the name.

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 description explains when results are meaningful, noting a fund needs two loaded quarters and that early on only a few are ranked, which guides expectations. It also explicitly points to a sibling, 'Use fund_track_record for the detail,' providing a concrete alternative. It does not enumerate other alternatives or edge cases, but the context it gives is useful and clear.

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