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get_airfoil_database

Access aerodynamic coefficients from an airfoil database to support aircraft performance analysis and flight planning calculations.

Instructions

Get available airfoil database with aerodynamic coefficients.

Returns: JSON string with airfoil database

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Main handler function for the 'get_airfoil_database' tool. Imports AIRFOIL_DATABASE from integrations and returns it as a formatted JSON string.
    def get_airfoil_database() -> str:
        """Get available airfoil database with aerodynamic coefficients.
    
        Returns:
            JSON string with airfoil database
        """
        try:
            from ..integrations.aero import AIRFOIL_DATABASE
    
            return json.dumps(AIRFOIL_DATABASE, indent=2)
    
        except ImportError:
            return "Airfoil database not available"
        except Exception as e:
            logger.error(f"Airfoil database error: {str(e)}", exc_info=True)
            return f"Airfoil database error: {str(e)}"
  • Registration of the get_airfoil_database tool (and related aerodynamics tools) in the FastMCP server.
    # Aerodynamics tools
    mcp.tool(wing_vlm_analysis)
    mcp.tool(airfoil_polar_analysis)
    mcp.tool(calculate_stability_derivatives)
    mcp.tool(get_airfoil_database)
  • Import of the get_airfoil_database handler from tools.aerodynamics.
    from .tools.aerodynamics import (
        airfoil_polar_analysis,
        calculate_stability_derivatives,
        get_airfoil_database,
        wing_vlm_analysis,
    )
  • The AIRFOIL_DATABASE dictionary containing coefficients for common airfoils, used by the tool handler.
    AIRFOIL_DATABASE = {
        "NACA0012": {
            "cl_alpha": 6.28,  # per radian
            "cl0": 0.0,  # zero-angle lift coefficient (symmetric)
            "cd0": 0.006,
            "cl_max": 1.4,
            "alpha_stall_deg": 15.0,
            "cm0": 0.0,  # symmetric airfoil
        },
        "NACA2412": {
            "cl_alpha": 6.28,
            "cl0": 0.25,  # zero-angle lift coefficient (cambered)
            "cd0": 0.007,
            "cl_max": 1.6,
            "alpha_stall_deg": 16.0,
            "cm0": -0.05,
        },
        "NACA4412": {
            "cl_alpha": 6.28,
            "cl0": 0.40,  # zero-angle lift coefficient (4% camber)
            "cd0": 0.008,
            "cl_max": 1.7,
            "alpha_stall_deg": 17.0,
            "cm0": -0.08,
        },
        "NACA6412": {
            "cl_alpha": 6.28,
            "cl0": 0.55,  # zero-angle lift coefficient (6% camber)
            "cd0": 0.007,
            "cl_max": 1.8,
            "alpha_stall_deg": 18.0,
            "cm0": -0.12,
        },
        "CLARKY": {
            "cl_alpha": 6.0,
            "cl0": 0.30,  # zero-angle lift coefficient (cambered)
            "cd0": 0.008,
            "cl_max": 1.5,
            "alpha_stall_deg": 14.0,
            "cm0": -0.06,
        },
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns a JSON string but does not describe the structure, size, or format of the database, whether it's read-only, or any performance considerations like caching or rate limits.

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

Conciseness3/5

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

The description is brief and front-loaded with the core purpose, but the 'Returns:' section is redundant since an output schema exists. It could be more concise by omitting the return statement or integrating it better, though it's not overly verbose.

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?

Given the tool has no parameters, annotations, but an output schema exists, the description is minimally adequate. However, it lacks details on the database content, update behavior, or integration with other tools, leaving gaps for an agent to understand full context.

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?

The tool has 0 parameters, and the input schema has 100% description coverage (empty object). The description does not need to add parameter details, so a baseline of 4 is appropriate, as it avoids redundancy while clearly indicating no inputs are required.

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?

The description clearly states the verb 'Get' and resource 'available airfoil database with aerodynamic coefficients', making the purpose evident. It distinguishes from siblings like 'get_propeller_database' by specifying the airfoil focus, but could be more explicit about what 'available' entails (e.g., pre-loaded vs. user-defined).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'get_propeller_database' or other aerodynamic tools. The description lacks context on prerequisites, such as whether the database needs to be loaded first, or typical use cases in the workflow.

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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