unflatten_json

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

No annotations are provided, and the description does not disclose behavioral traits such as error handling, return type, or side effects. It only describes the transformation without context on permissions or potential issues.

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 extremely concise: one sentence summarizing purpose followed by a clean parameter list. Every sentence adds value with no redundancy or filler.

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 tool's simplicity (input transformation) and the presence of an output schema (though not visible), the description covers the essential input format and separator. It does not address edge cases, but for a straightforward tool it is nearly complete.

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?

With 0% schema description coverage, the description effectively adds meaning by naming both parameters and explaining them: 'json_str' as 'Flattened JSON string' and 'separator' with default. This compensates for the lack of schema-level descriptions.

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 function with a specific verb ('reconstruct') and resource ('nested JSON from dot-notation flattened format'). It effectively distinguishes itself from the sibling 'flatten_json' by describing the inverse operation.

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 implies usage when dealing with dot-notation flattened JSON, but lacks explicit guidance on when to use this tool versus alternatives like 'flatten_json'. No exclusion criteria or prerequisites are mentioned.

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