ZenML MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic action ('List all stack components') without mentioning pagination behavior (implied by 'page' and 'size' parameters but not explained), rate limits, authentication requirements, or what happens with filtering parameters. This is inadequate for a tool with 9 parameters and no annotation coverage.

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 appropriately sized but not optimally structured. The first sentence clearly states the purpose, but the parameter documentation could be more integrated. While efficient, some sentences in the Args section are overly terse (e.g., 'The logical operator to use' without context), suggesting room for improvement in clarity without adding bulk.

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 (9 parameters, no annotations, but has output schema), the description is minimally adequate. It covers the basic purpose and documents all parameters, but lacks behavioral context, usage guidance, and explanation of how filtering works. The output schema existence means return values don't need description, but other gaps remain significant.

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 documents all 9 parameters with brief explanations. With 0% schema description coverage, this fully compensates by providing semantic meaning for each parameter. However, it doesn't explain parameter interactions (e.g., how 'logical_operator' works with filtering parameters) or format details (e.g., date formats for 'created'/'updated'), 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: 'List all stack components in the ZenML workspace.' It specifies the verb ('List') and resource ('stack components'), and provides scope ('in the ZenML workspace'). However, it doesn't differentiate from sibling tools like 'get_stack_component' or 'list_stacks', 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.

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_stack_component' (for single component retrieval) or 'list_stacks' (for listing stacks instead of components), nor does it specify prerequisites or exclusions. This leaves the agent without context for tool selection.

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