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RheaBose

ILP Drone Delivery MCP Server

by RheaBose

list_available_drones

Retrieve available drones with capabilities like capacity, heating, cooling, cost, and max moves to match delivery requirements and plan logistics.

Instructions

Get a list of all available drones with their capabilities (capacity, heating, cooling, cost, max moves)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hasCoolingNoFilter drones by cooling capability (true = only cooling drones, false = all drones)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the output ('list of all available drones with their capabilities') but does not specify whether this is a read-only operation, if it requires authentication, its rate limits, or pagination behavior. For a tool with no annotations, this leaves significant behavioral gaps, though it at least clarifies the return content.

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 a single, efficient sentence that front-loads the core purpose and lists the returned capabilities in parentheses. There is no wasted verbiage or redundancy, making it highly concise and well-structured for quick understanding.

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's low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It explains what the tool returns but lacks details on behavioral traits like safety or performance. Without annotations or an output schema, the description should ideally provide more context on the operation's nature, but it meets the basic requirement for a simple listing tool.

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?

The input schema has one parameter ('hasCooling') with 100% schema description coverage, fully documenting its purpose and type. The description does not add any parameter-specific information beyond what the schema provides, such as default behavior or interactions with other parameters. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

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 tool's purpose: 'Get a list of all available drones with their capabilities (capacity, heating, cooling, cost, max moves)'. It specifies the verb ('Get a list') and resource ('available drones'), and lists the returned capability fields. However, it does not explicitly differentiate from sibling tools like 'check_drone_availability' or 'get_drone_details', which might have overlapping or related functions.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'check_drone_availability' (which might check availability for specific drones) or 'get_drone_details' (which might retrieve details for a single drone), leaving the agent to infer usage context. There are no explicit when/when-not statements or prerequisites.

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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