Head-to-head

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

Beyond annotations (readOnly, idempotent), the description discloses meaningful behaviors: totals count only meetings with a known winner, walkovers/retirements are included, each meeting carries its outcome, and ambiguous names return candidate lists. This adds significant context for edge cases and data semantics, exceeding what annotations provide.

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 appropriately sized at four sentences, with the main purpose front-loaded. Every sentence serves a purpose: scope, name handling, counting methodology, and access requirement. No wasted words.

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 a clear output schema and only two simple parameters, the description covers the tool's purpose, data coverage, edge-case handling, and plan requirement. No significant gaps remain for an agent to select and invoke the tool 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?

The schema already documents both parameters with examples and minLength. The description adds that names are 'keys' and that ambiguous fragments return a candidate list, enriching the meaning of the name parameters beyond basic schema descriptions. Schema coverage is 100%, so this is a bonus.

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 the tool's purpose: 'The all-time record between two players,' specifying the data scope (archive 1968–2022 and completed matches 2023 onward). This distinguishes it from sibling tools like get_match or get_player, which focus on individual matches or player profiles.

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?

Provides clear context for when to use the tool: for head-to-head comparisons between two named players. It also explains the candidate-list behavior for ambiguous fragments. However, it does not explicitly name alternative tools or state when not to use this tool, only that it requires a BASIC plan.

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