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Labs64

Labs64/NetLicensing-MCP

netlicensing_get_license_template

Retrieve a specific license template from NetLicensing to configure software licensing parameters for your application.

Instructions

Get a specific license template.

Args: template_number: Template identifier

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
template_numberYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states a read operation ('Get'), implying it's likely safe and non-destructive, but doesn't confirm this or disclose other behaviors like authentication requirements, rate limits, error conditions, or what 'Get' entails (e.g., returns full template details). For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 brief and front-loaded with the core purpose ('Get a specific license template.'), followed by a simple Args section. There's no wasted text, but the structure is basic and could be more integrated (e.g., embedding parameter hints in the main description). It efficiently conveys essential information without redundancy.

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 (single parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and 0% schema coverage, it lacks behavioral context (e.g., safety, errors) and parameter details, making it incomplete for confident agent use. It relies heavily on the output schema and inferred context from sibling tools.

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 description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics by noting 'template_number: Template identifier', which clarifies the parameter's purpose beyond the schema's generic 'Template Number' title. However, it doesn't explain format (e.g., string pattern), sourcing (e.g., from list operations), or constraints, leaving the agent with incomplete guidance for correct invocation.

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 the resource 'a specific license template', making the purpose immediately understandable. It distinguishes from siblings like 'netlicensing_list_license_templates' by specifying retrieval of a single template rather than listing multiple. However, it doesn't explicitly contrast with other 'get' siblings (e.g., 'netlicensing_get_license'), leaving some ambiguity about resource specificity.

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 prerequisites (e.g., needing a template number), contrast with 'netlicensing_list_license_templates' for browsing, or specify use cases like retrieving template details for license creation. The agent must infer usage from the name and context alone.

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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