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. While it mentions the tool submits predictions, it doesn't describe what 'submission' entails - whether it's a write operation, if it requires specific permissions, what happens to existing submissions, or any rate limits. The return format is mentioned but not detailed.

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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value - the first establishes the core function, while the parameter and return explanations provide essential details without redundancy.

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?

For a submission tool with no annotations and no output schema, the description provides basic operational information but lacks important context about what submission means in this system, how it relates to challenges, or what the submission details dictionary contains. It's minimally adequate but leaves significant gaps.

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 meaningful context for both parameters: it specifies that file_path must be an absolute path ending with .parquet, and clarifies that slot is 1-based with a default of 1. With 0% schema description coverage, this compensates well by adding crucial semantic information beyond what the bare schema provides.

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 action ('Submit predictions') and resource ('from a Parquet file'), making the purpose evident. However, it doesn't explicitly distinguish this tool from its sibling 'submit_predictions_from_dataframe', which appears to serve a similar purpose with different input format.

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 the sibling 'submit_predictions_from_dataframe' or explain when file-based submission is preferred over dataframe-based submission, nor does it provide any prerequisites or context for when submission is appropriate.

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