ZenML MCP Server

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 mentions listing users but fails to describe key behaviors: whether this is a read-only operation, if it requires specific permissions, how pagination works, or what the output format is. The parameter list hints at filtering and sorting, but no explicit behavioral context is given.

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 structured with a clear purpose statement followed by a parameter list, but it's somewhat verbose due to repeating parameter names without additional value. Every sentence serves a purpose, but the parameter explanations are minimal and could be more integrated. It's adequate but not optimally efficient.

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 tool's complexity (7 parameters, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameters but lacks usage guidelines, behavioral details, and output information. The presence of an output schema reduces the need to explain return values, but overall, it leaves gaps for effective agent use.

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?

The description includes an 'Args' section that lists all 7 parameters with brief explanations, adding meaningful context beyond the input schema, which has 0% description coverage. This compensates well for the schema's lack of descriptions, though it doesn't provide detailed examples or constraints (e.g., date formats for 'created' and 'updated').

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: 'List all users in the ZenML workspace.' It specifies the verb ('List') and resource ('users in the ZenML workspace'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'get_user' or other list_* tools, 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.

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's no mention of sibling tools like 'get_user' for retrieving a single user or other list_* tools for different resources. It lacks context about prerequisites, such as authentication or workspace access, leaving usage unclear.

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