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 of behavioral disclosure. It states the tool sets frame ranges and returns a confirmation, but it does not cover critical aspects like whether this is a destructive operation (e.g., overwriting existing frames), permission requirements, or error conditions (e.g., invalid frame numbers). This leaves significant gaps in understanding the tool's 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 well-structured and concise, with a clear purpose statement followed by 'Args' and 'Returns' sections. Each sentence adds value: the first defines the tool's action, and the subsequent lines clarify parameters and output without redundancy. It is front-loaded and wastes no words.

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 (2 parameters, no annotations, but with an output schema), the description is fairly complete. It explains what the tool does, parameter meanings, and the return type. The output schema likely covers the confirmation details, so the description need not elaborate further. However, it could improve by addressing behavioral aspects like side effects or prerequisites.

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 meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'start' and 'end' are frame numbers and specifies the constraint 'end must be greater than start,' which is not in the schema. This compensates well for the lack of schema descriptions, though it could detail units or valid ranges more explicitly.

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 start and end frames of the scene timeline.' It specifies the verb ('Set') and resource ('scene timeline'), making the action explicit. However, it does not distinguish this tool from sibling tools like 'set_frame' or 'clear_animation', which could involve similar timeline operations, so it lacks sibling differentiation.

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 requiring an active scene or timeline, nor does it compare to siblings like 'set_frame' for single-frame operations or 'clear_animation' for resetting. Without this context, the agent must 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.