ZenML MCP Server

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 mentions 'List all run steps' but fails to describe key traits like pagination behavior (implied by 'page' and 'size' parameters but not explained), filtering logic (e.g., how 'logical_operator' applies), or response format. For a list tool with 11 parameters, this is a significant gap in transparency.

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

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

The description is front-loaded with the core purpose, but the parameter list is verbose and could be more efficiently structured (e.g., grouping related parameters). While not overly long, the formatting as a bullet-like list under 'Args:' is functional but not optimal for quick scanning, with some redundancy in parameter explanations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (11 parameters, no annotations) and the presence of an output schema (which reduces the need to describe return values), the description is partially complete. It covers parameters but misses behavioral context like filtering logic or pagination details. For a list tool with many filtering options, it should do more to guide usage and explain interactions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It lists all 11 parameters with brief explanations (e.g., 'sort_by: The field to sort the run steps by'), adding meaningful context beyond the schema's titles. However, it lacks details on parameter interactions (e.g., how 'logical_operator' combines filters) or value formats (e.g., date strings), preventing a perfect score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'List all run steps in the ZenML workspace,' which is a specific verb ('List') and resource ('run steps') with scope ('ZenML workspace'). However, it doesn't explicitly differentiate from sibling tools like 'get_run_step' (singular) or 'list_pipeline_runs,' leaving some ambiguity about when to use each.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 sibling tools like 'get_run_step' for single steps or 'list_pipeline_runs' for broader context, nor does it specify prerequisites or exclusions, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.