json_to_toonConvert JSON to TOON (Token-Oriented Object Notation), a compact format that uses about 40% fewer LLM tokens than JSON. Best for uniform arrays of objects.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | JSON document to convert (as a string) | |
| delimiter | No | Array delimiter (default comma) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered without description help. The description adds useful context that the output is roughly 40% smaller in tokens, but says nothing about failure modes for malformed JSON, size limits, or what is returned. Adds some value beyond annotations, not rich behavioral context.
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?
Two tight sentences with no filler: the conversion and format definition come first, the applicability hint second. Every clause carries information an agent needs.
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?
For a two-parameter, annotation-covered converter this is close to complete: the operation, the output format's purpose, and the best-fit input shape are all stated. Since no output schema exists, the description could have said more about the returned value (e.g. a TOON string) or error behavior on invalid JSON, which is the only real gap.
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?
Schema description coverage is 100%, with both 'json' and 'delimiter' (enum: comma/tab/pipe) documented in the schema itself. The description adds no detail about input format expectations or how the delimiter choice affects output, so the baseline 3 applies.
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 states a specific verb and resource ('Convert JSON to TOON') and defines the target format, so the direction of conversion is unambiguous. It never names its sibling toon_to_json to explicitly confirm it is the inverse operation, but the verb+resource pairing leaves no real ambiguity.
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?
'Best for uniform arrays of objects' gives a concrete applicability condition that tells the agent when this tool is a good fit. There is no when-not guidance and no explicit reference to the toon_to_json alternative, but the usage context is clear.
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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