create_equation_constraint

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Create', implying a mutation, but does not state whether the operation is additive, whether it modifies an existing model, what model_name defaults to, or whether there are side effects on existing constraints. The description also does not mention idempotency or failure behavior.

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 concise and front-loaded with the core purpose. The args section and example are compact and readable. It earns a 4 because it is efficient, though it sacrifices completeness for brevity.

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 is a modeling mutation with no annotations, and the description does not explain prerequisites (e.g., existing sets, model context), the nature of the constraint, or how it differs from related constraint tools. The output schema exists, so return values need not be described, but for a tool like this, more contextual guidance is needed for an agent to invoke it correctly in a real workflow.

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 0%, so the description must compensate. It documents the 'terms' parameter well, including the tuple structure and a concrete example. However, 'name', 'timeout', and 'model_name' are entirely unaddressed; their semantics rely on property names and defaults in the schema. Partial compensation for the most complex parameter, but incomplete overall.

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 states a specific verb and resource: 'Create a linear equation constraint.' This distinguishes it from sibling constraint tools like create_mpc_constraint, create_rigid_body_constraint, and create_tie at a category level, and the example clarifies the intended coupling of DOFs. It could be more explicit about what 'linear equation constraint' means in FEA, but it is not tautological or vague.

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?

There is no guidance on when to use this tool versus alternatives such as MPC constraints, rigid body constraints, or coupling constraints. The description does not mention prerequisites like existing sets or an active model, nor does it explain why an equation constraint would be preferred. An agent would have to infer usage from the tool name alone.

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