get_race_signals

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

No annotations are provided, so the description must carry the burden. It discloses the 'frozen model pick' and the conditional 'if the race made the public card', hinting at statefulness. However, it does not explain caching, error handling, or prerequisites, leaving some transparency gaps.

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 a single sentence that front-loads the core purpose and enumerates all key outputs. It is efficient, though slightly dense with specialized terms like 'de-overrounded', which is acceptable for the domain.

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 lists the available signals, which compensates reasonably. It falls short of describing the response structure or edge cases (e.g., invalid race_id, race not on the public card), leaving some completeness gaps.

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 covers the single 'race_id' parameter with a clear description and example. The tool description adds no additional parameter semantics, so the baseline score of 3 applies.

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 identifies the tool as returning derived signals for a single race, listing specific outputs like AI score, fair price, and value. It distinguishes this from sibling tools like get_today_races (list) and get_draw_bias (race-level verdict).

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 phrase 'for one race' implies usage for specific race analysis, but there is no explicit guidance on when to choose this over get_draw_bias or get_combo_stats. No alternatives or exclusions are mentioned, leaving usage to implication.

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