generate_blender_script

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

With no annotations, the description bears full responsibility for behavioral details. It only mentions script generation, omitting side effects (e.g., does it execute the script?), prerequisites (Ollama running), error handling, or return format. This leaves the agent underinformed.

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 a single short sentence, which is concise but overly terse. It front-loads the purpose but sacrifices necessary behavioral and parameter details, making it minimally adequate.

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?

Despite having an output schema (not shown), the description omits any mention of return values, script behavior, or integration with Blender. Given 3 parameters and no parameter descriptions, it leaves significant gaps for a generation tool.

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 0% and the description adds no parameter information. It does not explain the prompt format, model selection, or ollama_url usage, forcing reliance on default names and types without context.

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 tool generates a Blender Python script from a natural language prompt using Ollama, which is a specific verb-resource-method combination. It distinctively mentions 'local LLM (Ollama)', differentiating it from other AI-related sibling tools like blender_ai_generate.

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 explicit guidance on when to use this tool versus alternatives. It implicitly suggests usage via Ollama but fails to indicate prerequisites, use cases, or when to avoid it.

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