get_calibration

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

Without annotations, the description carries the burden. It explains that the tool returns metrics over a rolling window and the meaning of MAE and accuracy, but does not disclose if it is read-only or has side effects.

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 concise, with two sentences that front-load the main purpose. It includes helpful parenthetical clarifications, but slightly verbose with the Chinese phrasing.

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 explains the return components (MAE, accuracy, halves, improving boolean) but lacks detail on structure, types, or rolling window specifics. Adequate but not comprehensive.

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 has 100% parameter coverage with sessionId as the only parameter, but the description provides no explanation of this parameter. Schema coverage is 0%, and the description fails to add meaning beyond the schema.

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 returns calibration metrics (MAE and accuracy) within a rolling window, split into halves with an improving boolean. It specifies a distinct purpose, but does not explicitly differentiate from sibling tools like 'get_stats'.

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 mentions the tool is 'used to prove that as tasks increase, accuracy improves', giving some context. However, it lacks explicit guidance on when to use vs. alternatives, and no exclusion criteria.

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