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select_aerospace_tool

Analyzes an aviation task to recommend the optimal Aerospace MCP tool and provides step-by-step guidance for using it.

Instructions

Help select the most appropriate aerospace-mcp tool for a given task.

Uses GPT-5-Medium to analyze the user's task and recommend the best tool(s) along with guidance on how to use them.

Args: user_task: Description of what the user wants to accomplish user_context: Additional context about the user's situation (optional)

Returns: Recommendation with tool name(s) and usage guidance, including primary tool, secondary tools, workflow steps, and considerations.

Raises: No exceptions are raised directly; errors are returned as formatted strings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_taskYes
user_contextNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses use of GPT-5-Medium and that errors are returned as strings, but does not mention side effects, authentication, or model reliability.

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 concise, using a few sentences followed by clear args/returns/raises sections. Every part adds value without redundancy.

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 meta-nature and presence of output schema (not shown), the description covers purpose, parameters, return structure, and error handling, providing a complete picture for usage.

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 0%, but description compensates by describing both parameters (user_task and user_context) in detail, adding meaning beyond schema titles.

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 states the tool selects the most appropriate aerospace-mcp tool for a given task, using GPT-5-Medium. It clearly distinguishes from sibling calculation tools by being a meta-tool.

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?

The description implies when to use (when uncertain about tool choice) and provides guidance via args/returns, but lacks explicit when-not-to-use or alternatives, though no direct alternative exists on this server.

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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