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Zulelee

test-files-mcp

by Zulelee

create_csv_tool

Generate synthetic CSV test data streamed to disk, with control over rows, columns, and delimiters for creating test fixtures.

Instructions

Generate a CSV test fixture with synthetic data, streamed to disk.

Examples: 0 rows, 100,000 rows, 1,000,000 rows (within configured limits).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNo
seedNo
columnsNo
headersNo
encodingNoutf-8
filenameNo
delimiterNo,
overwriteNo
include_headerNo
output_directoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose that output is streamed to disk and that row counts are subject to configured limits, but it omits details about overwrite behavior, file naming/location, or failure behavior when limits are exceeded.

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

Conciseness4/5

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

The description is compact and front-loaded: the first sentence states purpose and key behavior, and the second sentence gives useful scale examples. It is free of fluff, though it could have used the space to cover more of the 10 parameters.

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 with 10 optional parameters, no annotations, and zero schema descriptions, the description is far too sparse. It does not explain how parameters interact (e.g., custom headers vs. column count), what the output schema contains, or what happens when overwrite=false and the file exists.

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

Parameters2/5

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

Schema description coverage is 0% for 10 parameters, yet the description only adds meaning to the 'rows' parameter via examples. Other parameters like seed, columns, headers, encoding, delimiter, overwrite, include_header, and output_directory receive no explanation or relationship context.

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 opens with a specific verb ('Generate'), a precise resource ('CSV test fixture'), and a key implementation detail ('synthetic data, streamed to disk'). This clearly distinguishes it from sibling tools like create_json_tool or create_pdf_tool, which target different file formats.

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

Usage Guidelines3/5

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

The description implies usage for CSV fixture generation, especially with the row-size examples (0, 100k, 1M rows). However, it never explicitly states when to prefer this over generic alternatives such as create_dummy_file_tool, nor does it mention when not to use it.

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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