JSON to TOON

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description usefully explains what TOON is and its token benefit, but says nothing about failure modes (invalid JSON input), size limits, or what the response looks like, so it adds only moderate context beyond the annotations.

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 sentences with no waste: the action and format come first, followed by the suitability guidance. The '43% fewer tokens' statistic is compact and decision-relevant rather than padding.

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 single-input converter with no nested objects, no output schema, and fully documented parameters, the definition covers everything strictly required to invoke it. It omits any note on the return type or error behavior for malformed JSON, which is a minor gap for a stateless conversion tool.

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%, so both 'json' and 'delimiter' are fully documented in the schema; the description supplies no additional parameter detail. The phrase about uniform arrays of objects weakly hints that delimiter matters for array rendering, but this is not explicit, 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?

States a specific verb and resource ('Convert JSON to TOON') and immediately defines the target format, so the direction of the transformation is unambiguous against the sibling toon_to_json. An agent can select this tool without opening the schema.

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 clear condition for when this tool is the right choice, which is real guidance rather than a restatement. It does not explicitly name toon_to_json as the reverse alternative or state when not to use it, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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. The description adds the useful detail that output is pretty-printed JSON, but says nothing about error behavior for malformed/unsupported TOON input, which is the main behavioral risk for a decoder.

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?

A single front-loaded sentence with zero filler; the action, input, and output format are all conveyed without waste.

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 trivial one-parameter conversion tool with no output schema, the description tells the agent the input type and the exact return format, which is essentially everything needed to call it. Only the failure mode for invalid TOON input is unaddressed.

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% for the single 'toon' parameter, so the schema fully documents the input. The description adds no syntax, format, or encoding detail beyond what the schema already states, making the baseline 3 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?

States a specific verb (Decode) and resource (a TOON document) plus the output format (pretty-printed JSON), which makes the direction of conversion unambiguous. It never names the sibling json_to_toon, so the differentiation is implicit rather than explicit, but 'back to JSON' makes the inverse relationship clear.

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?

Usage is implied by the direction stated in the description and the tool name; an agent can infer this is the TOON→JSON path. There is no explicit when-to-use statement, no mention of when not to use it, and no reference to the json_to_toon alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.