Convert a lab value between units

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

With no annotations, the description carries the full burden. It discloses key behaviors: accepts synonyms, converts to the other unit if to_unit omitted and only two units exist. However, it does not describe error handling for unsupported analytes, analytes with more than two units when to_unit is omitted, or the output format. Some edge-case transparency is missing.

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 two sentences, front-loaded with the main purpose, and includes valuable examples without fluff. Every sentence adds necessary context about synonyms and optional conversion behavior. Perfectly concise.

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 relatively simple tool with a complete schema and no output schema, the description covers the core functionality, parameter intent, and special optional behavior. It only lacks explicit handling of error/edge cases (e.g., analytes with >2 units and omitted to_unit), which would make it fully complete. Given the simplicity, it is nearly sufficient.

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 all four parameters with 100% coverage, so the baseline is 3. The description adds value by explaining the optional to_unit behavior (converts to the other unit if exactly two units) and provides analyte examples including a Russian synonym, enriching the schema's context.

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 converts a single blood-chemistry result between conventional and SI units, with concrete examples (glucose mg/dL <-> mmol/L, HbA1c % <-> mmol/mol). This verb+resource scope distinguishes it from siblings like identify_analyte and list_analytes, which serve different purposes.

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 gives clear context: use for single-result conversions between unit systems, with support for English/Russian synonym lookup and optional to_unit behavior. It does not explicitly exclude alternatives, but the focus on conversion and the sibling names make the intended use obvious. Lacks explicit 'when not to use' guidance.

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