blend-ai

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

No annotations are provided, so the description carries full burden. It states the tool sets the active camera and returns a confirmation dict, but lacks critical behavioral details: whether this is a destructive/mutative operation, permission requirements, error conditions (e.g., if the camera name doesn't exist), or side effects. This is a significant gap for a mutation tool with zero 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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured Args and Returns sections. There's no wasted text, though the 'Returns' line could be more informative (e.g., specifying what the confirmation dict contains).

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 moderate complexity (a mutation with one parameter), no annotations, and an output schema (though unspecified), the description is minimally adequate. It covers purpose and parameter semantics but lacks behavioral transparency and usage guidelines. The output schema existence means return values don't need explanation, but other gaps keep it from being complete.

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%, but the description adds basic semantics: 'name: Name of the camera object to make active.' This clarifies the parameter's purpose beyond the schema's generic 'Name' title. However, it doesn't specify format constraints (e.g., case sensitivity) or provide examples, leaving gaps. With one parameter, the baseline is 4, but the limited detail reduces it to 3.

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 active scene camera.' This is a specific verb ('Set') and resource ('active scene camera'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'set_camera_property' or 'point_camera_at', which might have overlapping or related functionality.

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 doesn't mention prerequisites (e.g., whether the camera must exist in the scene), exclusions, or comparisons to siblings like 'set_camera_property' or 'create_camera'. The agent must infer usage from context alone.

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