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 effectively describes the tool's behavior: it modifies properties of the active sculpt brush (indicating a mutation operation), specifies the exact properties that can be set and their value types/constraints, and mentions the return format ('Confirmation dict'). It lacks details on error conditions or side effects, but covers core behavior well for a tool with no annotations.

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 (Args, Returns) and uses bullet-like formatting for parameter details. It is front-loaded with the core purpose. Some minor verbosity exists (e.g., repeating 'Value to set' could be tighter), but overall it is efficient and every sentence adds value.

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, mutation operation), no annotations, and an output schema present (which handles return values), the description is complete. It covers purpose, parameters with semantics, and return format. The output schema existence means the description doesn't need to detail return values, and it adequately addresses the gaps from missing annotations and low schema coverage.

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 fully compensate. It does so excellently: it explains both parameters ('property' and 'value'), lists all valid property names (size, strength, auto_smooth_factor, use_frontface), and provides detailed value constraints (e.g., size is int 1-500, strength is float 0.0-1.0). This adds crucial meaning beyond the bare schema.

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 specific action ('Set a property') on a specific resource ('the active sculpt brush'), distinguishing it from sibling tools like 'set_sculpt_brush' (which likely selects brushes) and 'set_bone_property' or 'set_camera_property' (which target different resources). The verb+resource combination is precise and unambiguous.

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 implies usage context by specifying 'active sculpt brush', suggesting it should be used when sculpt mode is active and a brush is selected. However, it does not explicitly state when to use this tool versus alternatives like 'set_sculpt_brush' (which might change the brush type) or mention prerequisites (e.g., needing to be in sculpt mode). The guidance is present but incomplete.

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