agent-utils-mcp

tool_json_to_csv

Convert a JSON array into CSV text using a customizable delimiter. Turn structured JSON data into a tabular format for spreadsheets or data pipelines.

Instructions

Convert a JSON array to CSV text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "json_data": "<json_data>"
    },
    "name": "tool_json_to_csv"
  }
}

Input Schema

Name	Required	Description	Default
`delimiter`	No		,
`json_data`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the conversion direction and does not mention edge-case handling, quoting/escaping behavior, or requirements beyond 'JSON array'.

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?

One concise sentence with no filler, and the core conversion is front-loaded. It is efficient but slightly under-specified.

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?

For a simple two-parameter conversion tool, the description plus schema (required json_data, optional delimiter with default ',') is nearly complete. The output schema covers the return shape, so missing edge-case details are the only gap.

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%, so the description must compensate. It adds meaning to json_data by specifying it must be a JSON array, but it says nothing about the delimiter parameter or its default behavior, leaving a parameter gap.

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?

Description uses a specific verb ('Convert') and resource ('a JSON array' to 'CSV text'), and the direction clearly differentiates it from the sibling tool_csv_to_json. The word 'JSON array' gives a concrete input constraint.

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 use case is implied: call this when you have a JSON array and want CSV text. However, there is no explicit when-to-use, when-not-to-use, or mention of the reverse sibling tool_csv_to_json.

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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