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Skeego

opendata-mcp

by Skeego

compose_download_csv_v1_datasets__provider___dataset__compose_do

Download a composed join of two datasets as a CSV file. Specify the main dataset, target dataset, and join columns to stream the result.

Instructions

GET /v1/datasets/{provider}/{dataset}/compose/download.csv (public) — Download a composed join as CSV — Stream a composed CSV of provider/dataset joined with target.

Kept narrow for v1: single join, single join column, no computed columns, no filters. Mirrors the shape of POST /compose/preview so users can preview then download without tweaking parameters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerYes
datasetYes
targetYesJoin target dataset path (e.g. 'census/acs-5yr')
source_columnYesColumn in the main dataset to join on
join_columnYesColumn in the target dataset to join on
Behavior3/5

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

The description notes it's a GET request (public, streaming CSV) and lists current limitations (narrow v1). However, it does not explicitly confirm it's read-only or idempotent. With no annotations, the description partially addresses behavioral traits but lacks full transparency.

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 concise, two sentences plus a line, with the primary purpose front-loaded. Every sentence adds value, including the limitation note and reference to preview endpoint.

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

Completeness4/5

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

Despite no output schema or annotations, the description sufficiently explains the endpoint, its purpose, and constraints. It could mention response format or error handling but is adequate for a straightforward download tool.

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?

Input schema has 60% coverage (3 of 5 params have descriptions). The description adds no extra parameter meaning beyond the schema. It does not compensate for missing descriptions of provider and dataset.

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

Purpose5/5

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

The description clearly states the tool downloads a composed join as CSV, specifying HTTP method, public availability, and limitations (single join, no computed columns, no filters). It distinguishes itself from sibling tools like compose_preview.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains that this tool mirrors the shape of POST /compose/preview, enabling users to preview then download without tweaking parameters. It implies the preview endpoint is an alternative but does not explicitly state when not to use this tool.

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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