a1c_estimator

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

With no annotations, the description carries the behavioral burden. It discloses the computation method ('GMI from recent data weighted with historical HbA1c decay') and indicates reliance on existing CGM data. It does not mention edge cases or accuracy caveats, but there are no destructive or auth-related behaviors to disclose.

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?

Three short sentences, each with a distinct role: action, method, and use case. Front-loaded with the operative verb and contains no filler.

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?

For a three-optional-parameter estimator with no output schema, the description conveys the return concept (estimated future HbA1c) and a practical context (pre-lab visit). It leaves minor gaps around parameter pairing and exact return format, but the core calling context is adequately covered.

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 description coverage is 100%, so the baseline is 3. The description adds value by clarifying that the lab result is optional and by explaining the weighting logic behind the historical parameters. It does not explicitly state that last_a1c and last_a1c_date should be supplied together, which would have strengthened it.

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 opens with a specific verb and object ('Estimate future HbA1c') and names the inputs ('current CGM data and optional last lab result'). No sibling tool performs prediction, so this clearly distinguishes a1c_estimator from the surrounding read/analysis tools.

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?

It provides a clear use case: 'Useful before lab visits to set expectations.' It does not name alternative tools or exclusion conditions, but no sibling offers A1c estimation, so the context is sufficiently clear.

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