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by io.github.rwaldman

json_validate

Parse a string as JSON to confirm it is well-formed and return a normalized representation when possible before further processing or storage.

Use when:

  • Is this string valid JSON?

  • Parse and normalize a JSON payload before processing

  • Check whether agent or user-supplied text is well-formed JSON

Do not use when:

  • Validate against a specific JSON Schema or OpenAPI model beyond well-formedness

  • Encode or decode Base64 (use base64_encode / base64_decode)

  • Validate UUID or ISBN identifier formats

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes

TDQS

A3.9/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It mentions 'return a normalized representation when possible' but does not clarify what happens for invalid JSON (error, null, boolean?), nor the exact output format. The hedged 'when possible' adds ambiguity.

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 well-structured: a concise lead sentence followed by purposeful Use when/Do not use when bullets. No filler or redundant content.

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?

For a simple one-parameter tool, the description covers purpose and usage guidelines well. However, since there is no output schema, the return value and error handling are left unspecified. This is a notable gap for an agent deciding how to handle results.

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?

The schema has 0% description coverage, so the description must compensate for the single 'value' parameter. It implies the parameter is a JSON string ('Parse a string as JSON') but does not explicitly name 'value' or discuss edge cases like whitespace or encoding. Minimal compensation.

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 the tool parses a string as JSON to confirm well-formedness and return a normalized representation. It explicitly distinguishes itself from Base64, UUID, and ISBN validation tools via the 'Do not use when' section.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes explicit 'Use when' and 'Do not use when' sections, listing concrete scenarios and naming alternative tools (base64_encode/base64_decode, UUID/ISBN validators). This is exactly the guidance an agent needs.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct resource and action, with clear use cases and explicit 'Do not use when' guidance preventing confusion. For example, base64_decode and url_decode handle different encoding schemes, while timestamp_convert and timezone_convert address separate time operations.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern (e.g., base64_decode, country_lookup, uuid_validate). While verbs vary (decode, encode, lookup, validate, convert), the naming format is uniform and predictable.

Tool Count4/5

The 18-tool set is slightly above the typical 3-15 range, but the breadth is justified by the server's purpose as a general-purpose utility toolkit. Each tool earns its place, and the count does not feel overwhelming or redundant.

Completeness4/5

The toolkit covers encoding/decoding, validation, lookups, and conversions across common developer needs. Minor gaps exist, such as no UUID generation tool to complement uuid_validate, and no HTML entity encoding/decoding, but these are not critical omissions for the stated utility scope.

Resources