analyze_token_savings

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool analyzes 'potential token savings,' implying a read-only, non-destructive operation, but doesn't clarify if it requires specific permissions, how it calculates savings, or what the output format is. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is a single, clear sentence: 'Analyze potential token savings when converting JSON to TOON.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity.

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?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'token savings' means, how the analysis is performed, or what the result looks like (e.g., a percentage, comparison). For a tool with no structured output and minimal behavioral context, more detail is needed to be fully helpful.

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?

The input schema has 100% description coverage, with one parameter 'json_data' documented as 'JSON data to analyze for token savings.' The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score is 3, as the schema adequately handles parameter semantics.

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 clearly states the tool's purpose: 'Analyze potential token savings when converting JSON to TOON.' It specifies the action (analyze), the resource (token savings), and the context (conversion from JSON to TOON). However, it doesn't explicitly distinguish this analysis tool from its sibling conversion tools (convert_json_to_toon, convert_toon_to_json), which would require a 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools (convert_json_to_toon, convert_toon_to_json) or explain that this is for analysis before conversion, nor does it specify prerequisites or exclusions. The context is implied but not explicit.

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