blend-ai

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a mutation ('Set'), suggesting it modifies data, but fails to detail permissions, side effects, or error handling. No additional context like rate limits or confirmation details beyond the return statement is given, making it insufficient for safe invocation.

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 front-loaded with the core purpose, followed by clear parameter explanations. It avoids redundancy, but the 'Returns:' section could be more informative (e.g., specifying what 'Confirmation dict' contains), slightly reducing efficiency.

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 (3 parameters, mutation implied) and no annotations, the description covers parameters well but lacks behavioral context. The presence of an output schema mitigates the need to detail return values, but overall completeness is adequate with clear gaps in usage and transparency.

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 value beyond the input schema, which has 0% description coverage. It explains each parameter's purpose ('object_name: Name of the object', 'data_path: Property data path') and provides a crucial enum list for 'interpolation' with 13 specific types, compensating fully for the schema's lack of documentation.

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 action ('Set the interpolation type') and target ('for keyframes on a property'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'set_curve_property' or 'set_geometry_node_input', which could also involve property adjustments, leaving room for ambiguity in tool selection.

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?

No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites (e.g., needing existing keyframes) or comparisons to similar tools in the sibling list, such as 'set_curve_property' or 'insert_keyframe', leaving the agent without usage direction.

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