Prepare Study

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

Annotations already declare non-read-only, open-world, non-idempotent, non-destructive. The description adds the key behavioural fact beyond them: work is asynchronous, returns immediately with a jobId, and the artifact only appears after polling. It also discloses solver specifics (first-order BDF, explicit quiescent initial velocity) that the schema does not state.

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 sentences, front-loaded with the action and scope, then the kind-specific requirements, then the return/handoff. No filler and nothing repeated from structured fields verbatim.

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?

Output schema exists, so return values need not be spelled out; the description still gives the one fact that matters (jobId plus inspect_job). For a deeply nested six-variant physics schema it covers only the transient cases explicitly, leaving the steady, structural, modal, DC and steady-flow variants to the schema, which is acceptable but not exhaustive.

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 coverage is 100% for the single nested study parameter, so the baseline is 3. The description earns a bump by naming the per-physics-kind required inputs (density, heat capacity, initial temperature, timestep, step count) and the transient-flow discretisation, which reduces the need to reverse-engineer the oneOf branches.

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?

Names a specific verb chain (queue validation, meshing, solver-input generation) and the resource (a study), plus the background/async nature. It distinguishes itself from inspect_job by assigning polling to that sibling, though it never explicitly contrasts with validate_study or run_study, which are the closest neighbours.

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?

Establishes the workflow context: call this, then poll inspect_job until the prepared-study artifact exists. 'for an available study type' implies the study kind must be one the server supports. No explicit exclusions (e.g. validate first, or that this does not solve the study) are stated.

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