json_parse
Parse and validate JSON text
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | JSON text to parse |
Parse and validate JSON text
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | JSON text to parse |
Changes observed during successful MCP inspections.
Input schema / properties / argsRemoved value: -{
- "description": "Tool arguments",
- "properties": {
- "text": {
- "description": "Primary input text",
- "type": "string"
- }
- },
- "type": "object"
-}Input schema / properties / textAdded value: +{
+ "description": "JSON text to parse",
+ "type": "string"
+}Input schema / requiredPrevious value: -[]New value: +[
+ "text"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the operation but does not clarify what happens on invalid JSON, what the return format is, or how errors are signaled, which is a significant gap for a validation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is appropriately concise for a tool of this simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is not severely incomplete, but the lack of an output schema and annotations means it should explain the return/error behavior for validation. The description leaves some ambiguity, so it is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully describes the 'text' parameter, and the description does not add additional parameter-level meaning beyond reiterating that the input is JSON text. With 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (parse and validate) and resource (JSON text), which is specific and understandable. However, it does not explicitly distinguish it from sibling tools like json_flatten or extract_json that also operate on JSON, so it misses the top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The single sentence provides no context for tool selection, leaving the agent to infer usage.
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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