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Glama

avl.trim

Solve for angle of attack and one control deflection to achieve target lift and pitching moment coefficients at zero sideslip and body rates.

Instructions

Solve alpha and one existing CONTROL for target CL/Cm at zero beta/body rates. CONTROL values retain section gains, not automatically physical deflection degrees. Bounds accept/reject the native solution, not constrain iterations. Success requires residual/bounds checks and a fresh fixed-condition solve. Moments use the explicit geometry/override reference point, not an inferred CG. No mass/thrust balance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputsNo
requestYes
case_nameNotrim
model_pathYes
referencesNo
length_unitNounspecified
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.0

TDQS

A4.1/5.0
Behavior5/5

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

Goes well beyond annotations by disclosing that CONTROL values are section gains, that bounds accept/reject rather than constrain iterations, success requires residual/bounds checks and a fresh fixed-condition solve, and moments use the explicit reference point. No contradiction with annotations.

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?

Dense and front-loaded: purpose first, then caveats. Every sentence carries operational or domain meaning; no filler.

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?

For a complex trim solver with no output schema and 0% parameter-description coverage, the description covers purpose, scope, and success checks but omits return values and several parameter semantics, leaving gaps an agent would need to fill elsewhere.

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

Parameters3/5

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

Schema property description coverage is 0%, so the description must compensate. It clarifies the core scientific parameters (control semantics, bounds behavior, reference point) but leaves model_path, case_name, outputs, fixed_controls, tolerances, length_unit, and timeout_seconds unexplained.

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

Purpose4/5

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

States a specific verb (Solve) and the exact unknowns/targets: alpha and one existing CONTROL for CL/Cm at zero beta/body rates. It is clear but does not explicitly differentiate itself from siblings such as avl.sweep or avl.run.

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

Usage Guidelines4/5

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

Gives clear applicability constraints (zero beta/body rates, no mass/thrust balance) but does not name an alternative tool or explicitly say when to choose avl.trim over avl.sweep/avl.run.

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