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code-alchemist01

Development Tools MCP Server

parse_json

Parse JSON strings into structured data for development workflows, enabling code analysis and web scraping tasks.

Instructions

Parse JSON data

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesJSON string to parse

Implementation Reference

  • The handler logic for the 'parse_json' tool. It extracts the 'data' parameter, attempts to parse it as JSON using JSON.parse, and throws a descriptive error if parsing fails.
    case 'parse_json': {
      const data = params.data as string;
      try {
        return JSON.parse(data);
      } catch (error) {
        throw new Error(`Invalid JSON: ${error instanceof Error ? error.message : String(error)}`);
      }
    }
  • Registration of the 'parse_json' tool in the apiDiscoveryTools array, including its name, description, and input schema definition.
    {
      name: 'parse_json',
      description: 'Parse JSON data',
      inputSchema: {
        type: 'object',
        properties: {
          data: {
            type: 'string',
            description: 'JSON string to parse',
          },
        },
        required: ['data'],
      },
    },
  • Input schema for the 'parse_json' tool, specifying that it requires a 'data' string parameter.
    inputSchema: {
      type: 'object',
      properties: {
        data: {
          type: 'string',
          description: 'JSON string to parse',
        },
      },
      required: ['data'],
    },
Behavior2/5

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

No annotations are provided, so the description carries the full burden. 'Parse JSON data' implies a read-only operation that transforms input, but it doesn't disclose behavioral traits like error handling (e.g., invalid JSON), performance, or output format. For a tool with zero annotation coverage, this is a significant gap.

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 extremely concise ('Parse JSON data') with zero wasted words. It's front-loaded and efficiently communicates the core function in three words, making it easy for an agent to scan and understand.

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 no annotations, no output schema, and a simple parameter, the description is incomplete. It doesn't explain what the tool returns (e.g., parsed object, validation result) or error behavior, which are critical for an agent to use it correctly. The simplicity of the tool mitigates this somewhat, but key details are missing.

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%, with the parameter 'data' documented as 'JSON string to parse'. The description adds no additional meaning beyond this, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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 'Parse JSON data' clearly states the verb ('parse') and resource ('JSON data'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like parse_csv or parse_xml, but 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?

The description provides no guidance on when to use this tool versus alternatives like parse_csv, parse_xml, or validate_syntax. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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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