blender_python_exec_async

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

No annotations exist, so the description carries the burden. It discloses that execution is asynchronous, returns immediately, and supports cancellation detection via '__cancel_event__.is_set()'. It also hints at heavy resource use via 'long-running' and 'heavy scene generation'. However, it does not explicitly warn about potential side effects on the Blender scene or state that it modifies the scene, which is implied by script execution. This is a minor gap given the context.

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, well-organized paragraph that front-loads the core purpose, then covers the workflow, cancellation mechanism, ideal use cases, and a configuration tip. Every sentence adds value with no 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?

For a long-running async execution tool, the description covers the full lifecycle: what it does, how to obtain the job_id, how to poll and cancel, how to detect cancellation in the script, when it is appropriate to use, and a key configuration option. An output schema exists (though not shown) and the description already mentions the immediate return of job_id, which is sufficient. Nothing essential is missing for an agent to use the tool 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 description coverage is 0%, so the description must compensate for parameter meanings. It only mentions transport='headless' and defers to 'Same parameters as blender_python_exec'. This cross-reference is helpful only if the agent already knows the sibling tool's schema. No direct explanation of code, script_path, blend_file, timeout_seconds, or other parameters is provided, leaving the agent to infer or look elsewhere.

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?

Clearly states it starts a long-running Python script asynchronously, distinguishing it from the synchronous blender_python_exec. The verb 'start', resource 'Python script in Blender', and mode 'asynchronously' are all explicit, and the immediate return of a job_id is highlighted.

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?

Provides explicit guidance on when to use it ('Ideal for fluid baking, rigid body simulation, or heavy scene generation'), how to manage the job (poll with blender_job_status, abort with blender_job_cancel), and a specific usage tip (transport='headless' for background process). Clearly routes the agent to the appropriate workflow.

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