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avl.run

Run a prescribed flight condition to compute aerodynamic forces, stability derivatives, and surface loads with links to CSV/JSON output.

Instructions

Run one prescribed flight condition. Return forces, ST/SB derivatives, surface loads and links to strip CSV/JSON. Angles in degrees, rates nondimensional BODY axes; CONTROL values use gains defined in geometry. Default controls/rates zero. A references override changes only the staged copy. Ignores nearby .run/.mass.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputsNo
case_nameNocase
conditionNo
model_pathYes
referencesNo
length_unitNounspecified
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

With all annotations false, the description carries full behavioral burden. It discloses units (angles in degrees, rates in nondimensional body axes), defaults (controls/rates zero), override semantics (changes only the staged copy), and file interactions (ignores nearby .run/.mass). The only notable gap is whether execution is synchronous or queued, but the provided context is still strong.

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?

The description is four dense sentences with no filler. It front-loads the core purpose and outputs, then adds critical conventions, defaults, override semantics, and file-ignoring behavior. Every sentence earns its place.

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

Completeness4/5

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

For a 7-parameter tool with no output schema and no annotation support, the description covers outputs, units, defaults, override side effects, and file handling. It does not explicitly state what model_path should point to or whether the run is asynchronous, but these are largely inferable from the sibling tool set and the schema requirements.

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 description coverage is 0%, so the description must compensate. It adds meaning for condition parameters: angle/rate units, nondimensional body axes, control gains from geometry, and zero defaults. It also clarifies reference override scope. Parameters like outputs, case_name, length_unit, and timeout_seconds are left to schema/enum, but they are less ambiguous.

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 'Run one prescribed flight condition', a specific verb and resource, and enumerates concrete outputs (forces, ST/SB derivatives, surface loads, strip CSV/JSON links). This clearly differentiates it from sibling tools like avl.sweep (multiple conditions) and avl.submit (submission rather than direct run).

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 does not explicitly name alternatives or state when to use this tool vs avl.sweep or avl.submit, but 'one prescribed flight condition' implies a single-point analysis rather than a sweep. This is an implied usage signal rather than explicit guidance, so it earns a middle score.

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