pro_variant_study

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

Beyond the annotations, the description discloses that work happens on fresh saved copies, the source is never edited, dry_run defaults true and writes nothing, and the tool checks rebuilds/readbacks and produces evidence. This adds meaningful safety and execution context, though it does not cover idempotency behavior or limits.

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 five compact sentences, front-loaded with the core action and key constraints, and every clause carries useful information. The density is appropriate for a complex tool with no output schema.

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?

Because there is no output schema, the description usefully enumerates reported outputs: mass/volume, tight bounds, optional assertions, CSV/JSON evidence, and the lightest valid candidate. It also covers the source-safety and dry_run behavior, though it could say more about request_id, result_view, and assertion/parameter constraints.

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?

With 0% schema description coverage, the description compensates partially by explaining document_path as a self-contained saved .sldprt, parameters as explicit combinations, assertions as optional design assertions, and dry_run default/write behavior. It leaves request_id, result_view, assertion kinds/units, and the parameters array constraints unaddressed, so the compensation is incomplete.

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 uses a specific verb ('Evaluate'), resource ('explicit parameter combinations'), and scope ('fresh saved part copies'), making it clear this is a batch variant study rather than a single-feature edit. It does not explicitly differentiate itself by name from siblings such as pro_validate_design or pro_run_plan, so it falls short of a 5.

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 gives relevant prerequisites: a self-contained saved .sldprt, a clean source if open, and the guarantee that the source is never edited. However, it does not state when to choose this tool over adjacent tools like pro_validate_design or pro_run_plan, nor does it include exclusion cases.

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