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yade_execute_task

Execute a Python script asynchronously in YADE. Submit a script path and receive a task ID; the script runs in the background, queued sequentially for simulation.

Instructions

Submit a Python script for asynchronous execution in YADE.

Returns a task_id immediately; the script is queued and runs in the background. Tasks run one at a time in submit order (they share the YADE process and its single simulation state), so a multi-stage pipeline can be submitted in one go — each stage starts when the previous one finishes. Use the companion tools to manage the task lifecycle:

  • yade_check_task_status: poll output, progress, and final status

  • yade_interrupt_task: stop a running task or cancel a queued one

  • yade_list_tasks: browse task history (also shows queue order)

Use this for production simulation runs, long O.run() cycles, and any operation that may take minutes or longer. For quick queries and REPL-style testing, use yade_execute_code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYesBrief task purpose
script_pathYesAbsolute path to entry Python script for YADE

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description details asynchronous execution, immediate return, background queuing, and sequential ordering. No annotations provided, so the description carries full burden and does well, though it omits potential failure modes or authorization requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise and well-structured: tool purpose first, then behavior, companion tools, and usage guidance. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (async, queue, lifecycle), the description covers the key aspects: single-threaded execution, queue ordering, companion tools, and use case differentiation. Presence of output schema (context) covers return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. The description adds context: script_path is absolute, description is 'brief task purpose'. This enhances understanding beyond the schema field descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool submits a Python script for asynchronous execution, returns a task_id, and distinguishes itself from sibling tools like yade_execute_code by specifying use cases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says use for production runs and long operations, and advises using yade_execute_code for quick testing. Also explains the sequential queue behavior and lifecycle management.

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

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