generate_blender_script

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

With no annotations, the description should disclose behavioral traits. It mentions using a local LLM but omits critical details: what happens if Ollama is unavailable, whether it modifies the Blender scene, or what the return value is (though an output schema exists, its content is unknown).

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 sentence that is front-loaded and avoids fluff. It is concise, though it could benefit from slightly more detail without losing conciseness.

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 generating scripts with an external LLM, the description is incomplete. It does not address error scenarios, output format (despite output schema), or the interaction with other Blender tools. The lack of annotations and parameter descriptions exacerbates the gap.

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 add meaning. It only implicitly covers 'prompt' via the phrase 'natural language prompt'. It fails to explain 'model' (default 'llama3.2') and 'ollama_url' (default 'http://localhost:11434'), which are critical for tool usage.

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 verb 'Generate', the resource 'Blender Python script', and the method 'from a natural language prompt using a local LLM (Ollama)'. It effectively distinguishes from sibling tools like script_execute (which executes scripts) and list_local_models (lists models).

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, no prerequisites (e.g., Ollama running), and no exclusions. Users are left to infer usage context.

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