generate_simulation_spec

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

No annotations are provided, so the description carries full burden. It only mentions outputs but does not disclose behavioral traits like whether it is read-only, requires authentication, has rate limits, or if it modifies any state. This is insufficient for a tool with no annotation safety net.

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-loading the primary action and listing key outputs. Every sentence adds value without redundancy.

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?

Given the absence of an output schema, the description partially compensates by listing output categories, but doesn't specify if the output is structured as JSON or text. For a simple two-parameter tool with good schema coverage, this is adequate but not thorough.

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%, so the description does not need to explain parameters. It adds no extra meaning beyond what the schema's descriptions already provide for 'description' and 'cad_format'.

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 that the tool generates a structured simulation specification from natural language input, listing outputs like analysis types and mesh recommendations. It distinguishes from siblings like 'compare_materials' and 'get_material_properties' which focus on data retrieval, but it doesn't explicitly contrast with the generative sibling 'generate_dfm_checklist'.

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?

No guidance is provided on when to use this tool versus alternatives such as 'generate_dfm_checklist' or 'query_simulation_knowledge'. There is no mention of prerequisites, limitations, or when not to use it.

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