interpret_lab_report

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: item-by-item translation, reliance on specific guidelines (KDIGO, KDOQI, etc.), handling of discrepancies by listing options and deferring to local reference values, and output of red_flags and next_actions. This is substantive, though it could also mention how missing inputs are handled.

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 three concise sentences. The first sentence immediately captures the trigger and action. The second and third add valuable context about evidence sources, handling of disagreements, and output features without redundancy or filler. Every sentence earns its place.

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?

The tool has 21 parameters (all schema-described) and an output schema, so parameter and return details are covered elsewhere. The description fills in the purpose, use case, evidence basis, and behavior (red_flags/next_actions). It could be slightly more explicit about expected input combinations (e.g., which labs are needed), but overall it is complete enough for effective selection and invocation.

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 has 100% description coverage, so the baseline is 3. The tool description does not add any parameter-specific meaning beyond the schema; it only explains the overall purpose. The schema already documents each parameter's units and significance, so no deduction is warranted.

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 a specific verb ('translate') and resource ('lab report'), with a concrete trigger scenario ('when parents ask how to read it'). It distinguishes itself from sibling tools like translate_doctor_note (which handles notes) and explain_terms (which likely explains individual terms) by focusing on interpreting lab report items into plain language for parents.

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 explicitly says when to use ('when parents ask how to read the lab report'), which is clear context. However, it does not explicitly mention when not to use it or point to alternative tools (e.g., explain_terms for single terms), so it falls short of the highest bar.

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