get_handicap

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context beyond the schema by explaining the calculation method (best-N-of-20), the data requirements, and that the output includes both which rounds count and trend over time. This is a read-only operation and the description gives sufficient transparency about prerequisites and what the tool computes.

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 extremely concise, consisting of two sentences with no redundant information. The first sentence front-loads the core purpose and output, and the second sentence adds a crucial prerequisite. Every word earns its place, making it highly scannable for an AI agent.

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 the tool has no parameters and an output schema exists (so return values need not be described), the description covers all essential context: what the handicap index is, how it is calculated, the data needed, and that a trend is provided. It is complete enough for an agent to select and invoke the tool correctly, especially since there are no arguments to configure.

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 tool has zero parameters, so the baseline for this dimension is 4 as per the rubric. The description does not need to clarify parameter semantics because there are none. It instead focuses on the output and prerequisites, which 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?

The description clearly states this tool provides a WHS-style Handicap Index, detailing that it includes best-N-of-20 differentials, which rounds count, and index trend. This distinguishes it from sibling tools like get_club_stats or get_strokes_gained, which focus on other metrics. The resource (handicap index) and the specific outputs are unambiguous.

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 provides clear context about the prerequisite data: rounds with tee rating and slope, and notes that Garmin records these when a tee box is selected. This implicitly tells the user when this tool is usable but does not explicitly mention alternatives or when not to use it, so it falls short of a 5.

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