CrowdCent 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 states this is a read operation ('Get'), which is helpful, but doesn't mention important behavioral aspects like whether this requires authentication, rate limits, error conditions, or what specific details are included in the returned dictionary. The description is too minimal for a tool with 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 perfectly structured and concise. It begins with a clear purpose statement, then provides an 'Args' section with specific parameter guidance, and a 'Returns' section indicating the output format. Every sentence earns its place with no wasted words.

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 moderate complexity (single parameter read operation) and lack of both annotations and output schema, the description is minimally adequate but has clear gaps. It explains the parameter well and indicates a dictionary return type, but doesn't describe what specific details the dictionary contains or important behavioral constraints. The description does the basics but could provide more context for optimal agent usage.

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 provides excellent parameter semantics despite 0% schema description coverage. It clearly explains that 'version' accepts version strings like '1.0' or '2.1' and the special value 'latest', which adds crucial meaning beyond what the bare schema provides. This fully compensates for the lack of schema descriptions.

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 with a specific verb ('Get') and resource ('detailed information about a specific training dataset'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_training_datasets' or 'get_inference_data_info', which would be needed for 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 'list_training_datasets' (which might be used to discover available datasets first) or clarify the relationship between this tool and 'download_training_dataset'. There's no context about prerequisites or typical workflows.

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