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wayknow

wayknow/clearjson

validate_json

Check if a JSON string is valid, pinpoint errors to exact line and column, and get performance stats like node count and parse time.

Instructions

Validate a JSON string. Returns whether it is valid, and if not, the exact error location (line and column). Also returns stats: node count, max depth, file size, parse time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonYesThe JSON string to validate.
Behavior4/5

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

The description details return values: validity boolean, error location (line/column), and stats (node count, max depth, file size, parse time). It implies no side effects. With no annotations, this provides good transparency despite missing explicit read-only or safety hints.

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?

Two sentences: first for purpose, second for behavior. Every word adds value. No filler. Efficient and front-loaded.

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

Completeness5/5

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

For a simple one-parameter tool with no output schema, the description covers purpose, return values, and error details completely. No missing critical information.

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 coverage is 100% for the single parameter, and the schema already provides a clear description. The tool description does not add further meaning to the parameter, so baseline score is appropriate.

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 'Validate a JSON string' with a specific verb and resource, and distinguishes the return values including validation result and statistics. Even without siblings, the purpose is unambiguous.

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 or when not to use this tool. No mention of alternatives or context for use, which is a gap even for a simple tool.

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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