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Labs64/NetLicensing-MCP

netlicensing_get_licensee

Retrieve a specific customer's licensing information by providing their unique licensee identifier for management and verification purposes.

Instructions

Get a specific licensee (customer).

Args: licensee_number: Licensee identifier (e.g. 'I001')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
licensee_numberYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 this is a 'Get' operation, implying read-only behavior, but doesn't clarify authentication requirements, rate limits, error conditions, or what happens if the licensee doesn't exist. The description lacks critical behavioral context for a retrieval tool.

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

Conciseness4/5

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

The description is appropriately concise with two sentences: one stating the purpose and another explaining the parameter. It's front-loaded with the main purpose, though the parameter explanation could be integrated more smoothly rather than as a separate 'Args:' section.

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 (1 parameter) and the presence of an output schema (which handles return values), the description is minimally complete. However, it lacks behavioral details like error handling or authentication needs, and with no annotations, it doesn't fully compensate for those gaps in a read operation 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 description adds meaningful semantics beyond the schema: it explains that 'licensee_number' is a 'Licensee identifier' and provides an example format ('e.g. 'I001''). With 0% schema description coverage and 1 parameter, this adequately compensates by clarifying the parameter's purpose and format, though it could specify constraints like length or pattern.

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 as 'Get a specific licensee (customer)' with a specific verb ('Get') and resource ('licensee'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'netlicensing_get_licensee' vs 'netlicensing_list_licensees', though the distinction is implied by 'specific' vs 'list' naming.

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 doesn't mention when to choose this over 'netlicensing_list_licensees' for listing multiple licensees or 'netlicensing_update_licensee' for modifications, nor does it specify prerequisites or context for retrieval.

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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