blender

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

Annotations provide no hints (all false), but the description discloses critical behavioral traits: arbitrary Python execution, lack of sandboxing, unconstrained internal file operations, and the RCE risk. It also mentions headless execution and automatic GLB export, going well beyond what annotations or schema convey.

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 compact and front-loaded with purpose, then the action, then a crucial security warning. Every sentence earns its place, with no irrelevant filler.

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 executing arbitrary Python and no output schema, the description covers purpose, mechanism, risk, and output destination. It does not explain return values or error behavior, but the primary output (GLB file) is clear. The security context is thorough, making it sufficiently complete for an agent to invoke correctly.

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 schema already documents parameters. The description adds little semantic detail beyond mentioning action=execute_bpy and glb export to res://, which aligns with export_path but does not enrich understanding of code or timeout. It does not compensate significantly over the 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 'Blender procedural modeling' and specifies the action 'execute_bpy' with AI-written bpy snippets, headless execution, and automatic GLB export to res://. This distinguishes it from other tools by naming the exact resource and operation.

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 warns that bpy is full-featured Python with a threat surface of host RCE, an order of magnitude higher than the execute_gdscript sandbox, effectively cautioning when to use it versus safer alternatives. It also notes the local single-user trust model, but does not explicitly state functional use cases or exclusions beyond security concerns.

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