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

With no annotations, the description bears the full burden of behavioral disclosure. It states the input and output at a high level, but does not explain error handling on unrepairable input, the exact return type, or the scope of transformations applied.

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 sentence with no filler and front-loads the core action and result. Every word contributes to the tool's purpose.

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-parameter tool, the description provides a minimum viable explanation of what the tool does. However, the absence of annotations and output schema means the description should at least hint at error behavior or return format, which it does not.

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 schema provides 0% description coverage, but the single parameter 'input' is self-explanatory given the tool name and description. The description adds the context that the input is malformed JSON, though it does not elaborate on formatting expectations beyond the schema's string type.

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 uses a specific verb ('Repair') with a clear resource ('common malformed JSON') and states the outcome ('return valid structured JSON'). This clearly distinguishes it from the unrelated sibling tools like entity_normalize and network_capabilities.

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 the tool should be used when malformed JSON input needs to be corrected, which is meaningful but not explicit. It does not state when to avoid using it, mention alternatives, or describe limitations such as which malformations are covered by 'common'.

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