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ZenML MCP Server

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by zenml-io

get_service

Retrieve detailed information about a specific service by providing its name, ID, or prefix to access service configuration and status within the ZenML platform.

Instructions

Get detailed information about a specific service.

Args:
    name_id_or_prefix: The name, ID or prefix of the service to retrieve

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
name_id_or_prefixYes

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 the full burden of behavioral disclosure. While 'Get detailed information' implies a read-only operation, it doesn't specify authentication requirements, rate limits, error conditions, or what 'detailed information' includes. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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: a clear purpose statement followed by parameter documentation. The structure is front-loaded with the main purpose. However, the parameter documentation could be slightly more integrated rather than a separate 'Args:' section, and there's room to add usage guidance without sacrificing conciseness.

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 that there's an output schema (which handles return values), no annotations, and a simple single-parameter input, the description is minimally adequate. It covers the purpose and parameter semantics but lacks usage guidelines and behavioral details. For a retrieval tool in a context with many sibling tools, more contextual guidance would be beneficial.

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 context for the single parameter: 'name_id_or_prefix: The name, ID or prefix of the service to retrieve.' This clarifies that multiple identifier types are accepted, which is valuable since schema coverage is 0% and the schema itself provides no description. With only one parameter, the baseline is 4, and the description fully compensates for the lack of schema documentation.

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 detailed information about a specific service.' It uses a specific verb ('Get') and resource ('service'), and the 'detailed information' qualifier adds useful context. However, it doesn't explicitly distinguish this from sibling tools like 'list_services' or 'get_service_connector', which would require a 5.

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. There are multiple sibling tools that might be relevant (e.g., 'list_services' for listing all services, 'get_service_connector' for related resources), but the description doesn't mention any of them or provide context about when this specific retrieval tool is appropriate.

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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