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crowdcent

CrowdCent MCP Server

Official
by crowdcent

download_meta_model

Download the consolidated meta model for CrowdCent prediction challenges to a specified .parquet file path, enabling access to challenge data structures.

Instructions

Download the consolidated meta model for the current challenge.

Args:
    dest_path: Absolute path where to save the meta model, must end with .parquet

Returns:
    Success message or error

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dest_pathYes
Behavior2/5

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 the action 'download' and a success/error return, but lacks details on permissions, rate limits, file format specifics, or what happens if the path is invalid. This is inadequate for a tool that writes files to the filesystem.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by structured Args and Returns sections. Every sentence adds value without redundancy, making it efficiently sized and well-organized for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (file download with path constraints), lack of annotations, and no output schema, the description is incomplete. It misses critical details like authentication needs, error conditions, or what the meta model contains, leaving significant gaps for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context for the single parameter 'dest_path', specifying it must be an absolute path ending with .parquet, which goes beyond the schema's basic string type. With 0% schema description coverage and only one parameter, this compensates well, though it doesn't explain the .parquet requirement further.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'download' and the resource 'consolidated meta model for the current challenge', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'download_inference_data' or 'download_training_dataset' beyond mentioning the specific resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 prerequisites (e.g., needing an active challenge), exclusions, or comparisons to similar tools like 'get_challenge_info' or other download tools, leaving usage context unclear.

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

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