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 discloses that this is a mutation operation ('Set an input value') and hints at the return format ('Confirmation dict'), but lacks details on permissions, error handling, or side effects. The description adds some behavioral context but is incomplete 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 well-structured with clear sections for 'Args' and 'Returns', and every sentence adds value. It's front-loaded with the core purpose and efficiently details parameters without redundancy, 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 complexity of a mutation tool with 4 parameters, 0% schema coverage, and no annotations, the description does a good job explaining parameters and the return value. However, it lacks details on behavioral aspects like error cases or prerequisites. The presence of an output schema helps, but more context on usage and constraints would improve completeness.

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%, so the description must compensate. It effectively explains all four parameters: 'object_name', 'modifier_name', 'input_name', and 'value', including type dependencies for 'value'. This adds significant meaning beyond the bare schema, though it could provide more examples or constraints.

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 an input value') and target resource ('on a geometry nodes modifier'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'set_modifier_property' or 'list_geometry_node_inputs', which would require more specific context about when to use this particular tool versus those alternatives.

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., needing an existing geometry nodes modifier), exclusions, or comparisons to sibling tools like 'set_modifier_property' or 'list_geometry_node_inputs'. Usage is implied but not explicitly stated.

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