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process_json

Prettify, validate, or minify JSON strings for debugging, formatting API responses, or verifying syntax.

Instructions

Prettify, validate, or minify a JSON string.

Use this for debugging, formatting API responses, cleaning up configuration
files, or verifying that a string is valid JSON.

Parameters:
    json_string — The JSON string to process (required). Pass the raw JSON text.
    mode        — Operation: "prettify" (indent + sort keys), "validate"
                  (check syntax only), or "minify" (compact, no whitespace)
                  (default: "prettify").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
json_stringYes
modeNoprettify

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description adequately explains that the tool processes JSON strings and the modes affect output. However, it does not disclose error handling (e.g., what happens with invalid JSON in minify mode) or return format. With no annotations, more detail on behavior would be beneficial.

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 with a single introductory line followed by a clear, parameter list. It is front-loaded with purpose and uses minimal words effectively.

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?

Given the tool's simplicity and the presence of an output schema, the description covers purpose, parameters, and use cases adequately. Minor omissions like input size limits or return value details are not critical but could be added.

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

Parameters4/5

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

The schema itself has no parameter descriptions (0% coverage), so the description compensates well by explaining that 'json_string' requires raw JSON text and listing the three mode options with defaults. This adds significant meaning beyond the schema.

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

Purpose4/5

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

The description clearly states three specific operations (prettify, validate, minify) and lists concrete use cases like debugging and formatting. However, it does not explicitly differentiate from sibling tools such as 'validate_json' or 'code_beautify', which may overlap.

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 provides context by listing appropriate use cases, but it does not offer when-not-to-use guidance or mention alternatives. No explicit exclusions are given, which would help the agent avoid misuse.

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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