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. It discloses that the tool returns JSON with pagination metadata, which is useful behavioral context. However, it doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, or error conditions, leaving gaps in behavioral understanding.

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 well-structured with a clear purpose statement followed by return value and parameter details. It's appropriately sized for an 8-parameter tool, though the parameter explanations are somewhat terse and could be more front-loaded with critical information.

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 (8 parameters, no annotations, but has output schema), the description is reasonably complete. It explains the purpose, return format, and parameters. The output schema handles return values, so the description doesn't need to detail them further. However, it lacks guidance on tool selection and some behavioral aspects.

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 schema description coverage is 0%, so the description must compensate. It lists all 8 parameters with brief explanations (e.g., 'Filter by creation date'), adding meaningful semantics beyond the bare schema. However, it doesn't provide format details (e.g., date format for 'created') or explain parameter interactions, 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 verb ('List') and resource ('projects in the ZenML workspace'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_project' (singular retrieval) or 'list_artifacts' (different resource type), 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. It doesn't mention sibling tools like 'get_project' for retrieving a single project or context about when listing is preferred over direct retrieval. Usage is implied but not explicitly stated.

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