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avl.submit

Submit AVL aerodynamic analysis jobs asynchronously, returning a job ID for immediate retrieval. Supports up to 10,000 cases with background execution that survives client disconnects.

Instructions

Snapshot inputs and start a detached local AVL job; return job_id immediately. 1-10000 cases, at most two background workers execute per work root. Workers survive MCP client disconnection. Timeout is the execution budget per attempt, excluding queue. outputs=['total'] skips derivatives/surface/strip output; None requests all tables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputsNo
case_nameNojob
conditionsYes
model_pathYes
referencesNo
length_unitNounspecified
stop_on_errorNo
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior4/5

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

With all annotation hints false, the description carries the full burden. It discloses meaningful behaviors: detached execution, workers surviving MCP client disconnection, timeout semantics ('per attempt, excluding queue'), and outputs behavior. This goes well beyond the sparse annotations, though it omits details about input snapshot effects or error handling.

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?

Three dense sentences front-load the core purpose and immediately follow with key constraints. Every sentence adds value: execution model, worker behavior, timeout scope, and output shorthand. No filler or redundancy.

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

Completeness3/5

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

The description covers the job execution model and a couple of parameters, but with 8 parameters, no output schema, and no annotation support, there are gaps. It does not explain how to pass conditions/references or what stop_on_error does, nor how to later retrieve results (though sibling tools exist). It is minimally viable but not fully complete.

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

Parameters2/5

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. It does explain 'outputs' and 'timeout_seconds' partially, but does not clarify 'model_path', 'conditions', 'references', 'length_unit', 'stop_on_error', or 'case_name'. For an 8-parameter tool, this is insufficient compensation.

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 opens with a clear verb and resource: 'Snapshot inputs and start a detached local AVL job; return job_id immediately.' It distinguishes the tool from siblings like avl.run by emphasizing the detached/asynchronous nature and immediate return, so an agent can tell it apart without inspecting other tools.

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

Usage Guidelines3/5

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

The description implies usage for detached background execution, but it never explicitly names alternatives or states when not to use this tool. It does not mention that avl.run might be the synchronous counterpart or provide exclusion criteria, leaving the choice to inference.

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