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

Annotations already declare a safe, idempotent, closed-world read, so the description is free to add real value — it discloses that the result carries an observed-CL band and applicability warnings, and flags the predicted-input provenance obligation. It stops short of describing the warning conditions or the return shape, but the added context is genuine.

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?

Two sentences, zero filler. The computational purpose is front-loaded, and the provenance caveat follows as a secondary instruction. Nothing could be cut without losing meaning.

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 9-parameter IVIVE calculator with no output schema, the description covers the computational basis, the presence of an observed-CL band and warnings, and the prediction-provenance duty. It could say more about what the warnings or band represent, but an agent has enough to call it correctly and interpret the response at a high level.

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 every parameter (including rb, model, assay_type, correction_id, clint_censored) is already documented in more detail than the description provides. The description names the key inputs but adds no syntax, units, or constraints beyond the schema — the baseline 3 applies.

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?

States a specific computed resource (hepatic and plasma clearance) and the exact inputs driving it (in-vitro CLint, fu,mic, fu,p, IVIVE), plus what comes back (observed-CL band, applicability warnings). That is enough to separate it from siblings such as scale_to_human or target_clint without opening the schema.

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?

One explicit workflow rule is given: if fu,p or fu,mic came from predict_inputs, surface the predicted-input caveat. There is no guidance on when to choose this tool over scale_to_human or target_clint, so selection between siblings is only implied by the input signature.

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