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flatten_json

Convert nested JSON objects into dot-notation key-value pairs for simplified data access and transformation.

Instructions

Flatten nested JSON to dot-notation key-value pairs.

Parameters:
    json_str — JSON string to flatten.
    separator — Separator (default: '.').

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_str": "<json_str>"
    },
    "name": "flatten_json"
  }
}

Input Schema

Name	Required	Description	Default
`json_str`	Yes
`separator`	No		.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.4.1Jun 22, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations provided, so the description carries full burden. It only states the basic operation and mentions the separator default, but it does not disclose how arrays are handled (e.g., array indices), what happens with invalid JSON, circular references, or non-object types. This is insufficient for predictable invocation.

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 very short and front-loaded with the core action. It uses a bullet list for parameters. While efficient, it could be more structured (e.g., separate the description from parameter details). Nearly conciseness-perfect with minimal waste.

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

Completeness3/5

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

The tool is simple with only two parameters and no output schema provided in the description (though context says one exists). The description covers essential purpose and parameters but lacks details on return format, error behavior, and edge cases. Adequate but not complete given the lack of annotations.

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 0%, so the description must compensate. It briefly explains both parameters: json_str is the JSON string, separator is the delimiter (with default). This adds some value but does not explain constraints like valid JSON format or acceptable separator characters.

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?

Clearly states the tool flattens nested JSON to dot-notation key-value pairs. This is a specific verb+resource combo that distinguishes it from siblings like unflatten_json (which does the inverse) and process_json (general JSON processing).

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 when you need to flatten JSON, but it does not explicitly state when to use over alternatives, nor does it mention when not to use it. No exclusions or context for selecting this tool over related tools like unflatten_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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