set_recall_precision

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

With no annotations provided, the description carries full burden and does well: it explains the mapping from precision levels to beta values, override behavior, clearing logic, immediate persistence, and that no restart is needed. Minor omission of potential errors or return behavior prevents a 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?

The description is front-loaded with the core purpose and every subsequent sentence adds necessary detail. Slightly verbose but well-structured and informative. Could be tightened slightly without losing clarity.

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 no output schema, the description lacks information about the return value (e.g., success indicator or new threshold). Also does not cover error conditions like invalid agent_id. Otherwise, the effect and behavior are thoroughly described.

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 coverage is 100% but description adds significant value by explaining the numeric mapping (strict=2.0, etc.), interaction between precision and beta, and the clearing override case, which goes well beyond the schema descriptions.

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?

Description clearly states the verb 'Set', the resource 'agent's recall precision', and distinguishes it as a per-agent setting rather than per-recall argument, differentiating it from siblings like recall and calibrate_threshold.

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?

While the description explains what the tool does in detail, it does not provide explicit guidance on when to use this tool versus alternatives such as calibrate_threshold or get_recall_precision. The context is clear but lacks when-not-to-use advice.

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