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Parse JSON under safety limits

is-json-safe
Read-onlyIdempotent

Parse JSON with bounded depth, key counts and input size. Use to screen JSON without execution; use optimize-dataset for JSONL or CSV cleanup. Returns {ok, issues, bytes, depth, keys, value?}; parsed value is included only when valid.

Input Schema

NameRequiredDescriptionDefault
jsonYesJSON document as a string, up to 4096 characters; depth and key counts are limited.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / json / description
      Added value: +"JSON document as a string, up to 4096 characters; depth and key counts are limited."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), but the description adds real value: parsing runs without execution, limits are enforced on depth/keys/size, and the returned value is conditional on validity. The specific limit thresholds are not quantified, which keeps this short of a 5.

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?

Three short sentences, front-loaded with the action, then routing, then return shape. No filler or redundant restatement of the name.

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?

With no output schema, the description compensates by naming the return fields ({ok, issues, bytes, depth, keys, value?}) and the condition under which value appears. Combined with the routing hint, an agent has everything needed to call and interpret this tool.

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% for the single 'json' parameter, so the baseline is 3. The description's mention of bounded depth, key counts and input size mirrors what the schema already documents rather than adding syntax or format guidance.

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?

Specific verb+resource with scope: parse/screen JSON under bounded depth, key counts and input size. It explicitly names the sibling it is not (optimize-dataset for JSONL/CSV), so an agent can route correctly without opening either schema.

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?

States when to use it ('screen JSON without execution') and names the concrete alternative plus its condition ('use optimize-dataset for JSONL or CSV cleanup'). Nothing is left to inference about tool selection.

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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