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openascot

CKAN MCP Server

by openascot

download_dataset_locally

Download datasets from CKAN open-data portals to your local filesystem for offline analysis and processing.

Instructions

Download a dataset resource, metadata, and usage guide to the local filesystem using curl

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageIdYesThe dataset ID or name to download
resourceIdNoOptional ID of the specific resource to download
preferredFormatNoPreferred resource format to download (CSV, JSON, etc.)
downloadTimeoutSecondsNoMaximum time allowed for the curl download
Behavior2/5

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. While it mentions the curl implementation and implies local filesystem storage, it doesn't describe what happens during download (e.g., file naming, directory structure, error handling), whether authentication is needed, or what happens if downloads fail. For a tool that writes to local filesystem with multiple parameters, this is insufficient behavioral context.

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 a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for the tool's complexity and front-loads the essential information about what the tool does and how it works.

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?

For a tool that downloads datasets to local filesystem with 4 parameters and no annotations or output schema, the description is incomplete. It doesn't explain what gets downloaded (beyond 'resource, metadata, and usage guide'), where files are saved, how they're organized, or what happens on success/failure. The agent lacks sufficient context to use this tool effectively without trial and error.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. The baseline of 3 is appropriate when the schema does all the parameter documentation work.

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 action ('Download') and target ('dataset resource, metadata, and usage guide') with implementation method ('using curl'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_package' or 'get_resource_records' which might retrieve similar content without local storage.

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, when this tool is appropriate versus other dataset retrieval tools, or any constraints on usage. The agent must infer usage context from the tool name and description alone.

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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