blender_validate_dimensions

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

No annotations are provided, so the description must carry the full burden. It does describe the output format (per-axis pass/fail with deviations), but it does not disclose whether the operation is read-only or if there are any side effects. It also does not mention behavior when the object is not found.

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 with no fluff, front-loading the main action and result. It is concise and well-structured.

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 description provides enough context for an agent to understand the tool's purpose and output, but it lacks details on edge cases like missing objects or error handling. Since there is no output schema, the description gives a high-level return description but not a precise format.

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?

The schema covers 100% of parameters with descriptions, so the description adds little beyond what is already in the schema. It mentions 'configurable tolerance' and 'per-axis' which are also in the schema, so it doesn't add substantial new meaning.

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 the tool checks an object's bounding-box dimensions against expected values with tolerance, and reports per-axis pass/fail with deviations. It is specific and distinguishes from siblings like blender_measure which likely measure actual dimensions.

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?

The description implies usage for validation scenarios but does not explicitly differentiate from alternatives like blender_measure or mention when not to use it. It provides context but no exclusions.

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