blender_calibrate_from_reference

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

With no annotations provided, the description carries the behavioral disclosure burden. It explicitly states the object is scaled uniformly and that transforms are applied afterward so the scale returns to (1,1,1), revealing the post-condition and mutation behavior. It could mention prerequisites such as object existence, but the core side effects are transparent.

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?

Two sentences deliver the essential action, purpose, and post-condition with no filler. The key operation is front-loaded, and the second sentence adds meaningful behavioral detail without redundancy.

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?

The description is sufficient given the 100% schema coverage and the tool's moderate complexity. It explains the operation, the result, and the coordinate/unit context well enough for an agent to invoke it correctly. It does not describe return values or error conditions, but no output schema exists and the operation's outcome is clearly stated.

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 coverage is 100%, so the input schema already fully documents all parameters. The description reinforces the concepts of 'known dimension' and 'chosen axis' but does not add new semantic detail beyond the schema, matching the baseline of 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 states a specific verb ('Scale'), a resource ('an object'), and the exact purpose: matching a known real-world dimension along a chosen axis. It also distinguishes itself from generic transform tools by noting it applies transforms afterward so scale returns to (1,1,1), making the tool's specialized behavior clear.

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 clearly implies when to use it: when an object needs to be calibrated so a real-world measurement matches along a specific axis. It does not explicitly name alternatives like blender_object_transform or state when not to use it, but the specialized calibration context is unambiguous.

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