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ZenML MCP Server

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by zenml-io

get_pipeline_details

Retrieve detailed information about a specific ZenML pipeline, including recent run statuses, to monitor and analyze pipeline execution.

Instructions

Get detailed information about a specific pipeline.

Args:
    name_id_or_prefix: The name, ID or prefix of the pipeline to retrieve
    num_runs: The number of runs to get the status of

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
name_id_or_prefixYes
num_runsNo

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' implies a read operation, the description doesn't mention 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 sized with three sentences: a clear purpose statement followed by parameter explanations. It's front-loaded with the main purpose and avoids unnecessary fluff. The parameter explanations could be slightly more integrated, but overall it's efficient.

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) and no annotations, the description provides basic purpose and parameter semantics. However, for a tool that retrieves 'detailed information' with behavioral implications, it should include more about authentication, error handling, or what 'detailed' entails to be fully complete.

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 descriptions. The description compensates by explaining both parameters: 'name_id_or_prefix' as 'The name, ID or prefix of the pipeline to retrieve' and 'num_runs' as 'The number of runs to get the status of'. This adds meaningful semantics beyond the bare schema, though it doesn't cover format details or constraints.

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 with a specific verb ('Get') and resource ('detailed information about a specific pipeline'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_pipeline_run' or 'list_pipelines', which prevents a perfect score.

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. With sibling tools like 'get_pipeline_run' (for individual runs) and 'list_pipelines' (for multiple pipelines), the agent lacks context on when this specific detailed retrieval is appropriate versus those other options.

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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