blend-ai

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

No annotations are provided, so the description carries the full burden. It implies a mutation operation ('Set'), but does not disclose behavioral traits like whether it requires specific permissions, if changes are reversible, or potential side effects. The return value is mentioned, but lacks details on error handling or performance. This is a moderate gap for a mutation tool with no annotation coverage.

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 well-structured and concise, using bullet-like sections for Args and Returns. Each sentence adds value: the purpose is stated upfront, parameter details are organized efficiently, and return information is included without redundancy. There is no wasted text, making it easy to scan and understand.

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 tool's complexity (a mutation with 3 parameters) and no annotations, the description does a good job covering parameters and return values, especially since an output schema exists. However, it lacks context on usage guidelines and behavioral transparency, such as error conditions or when to use alternatives, leaving some gaps in completeness for effective tool selection.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains the 'rotation' parameter's format for EULER and QUATERNION modes, specifies units (radians), and clarifies the 'mode' parameter's default and allowed values. This compensates fully for the schema's lack of descriptions, making parameters clear and actionable.

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's purpose: 'Set the rotation of an object.' It specifies the verb ('Set') and resource ('rotation of an object'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'set_location' or 'set_scale', which are similar transformation tools, so it misses full sibling distinction.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as whether the object must exist or be selected, or compare it to other transformation tools like 'set_pose' or 'apply_transforms'. Without such context, users may struggle to choose appropriately.

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