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oh-my-mcp

oh-my-mcp

by quyansiyuanwang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

json_to_csv

Convert a JSON array of objects to a structured CSV file for data analysis.

Instructions

Convert JSON array to CSV format.

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_string": "<json_string>"
    },
    "name": "json_to_csv"
  }
}

Input Schema

NameRequiredDescriptionDefault
json_stringYesJSON string (must be array of objects)

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

The description provides no behavioral details beyond the verb 'convert'. With no annotations, it fails to disclose what happens with invalid input, nested objects, or key mismatches. The input schema partially covers input validation, but the description adds no safety or side-effect context.

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 a single sentence with no waste. However, it could be slightly expanded to include input constraints or output details without losing conciseness.

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 existence of an output schema, the description might rely on that for return format. Still, it lacks contextual details like error handling, supported CSV dialect, or behavior with huge arrays. The description is too minimal for a complete understanding.

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% for the single parameter. The description 'Convert JSON array to CSV format' does not add extra meaning beyond the schema's 'JSON string (must be array of objects)'. Baseline score of 3 applies.

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 action (Convert), the input (JSON array), and the output (CSV format). It effectively distinguishes from sibling tools like csv_to_json or json_to_yaml.

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?

No guidance on when to use this tool versus alternatives. For instance, it does not mention that the input must be a JSON array of objects, nor does it suggest other tools for different JSON structures.

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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