map_reduce_mr_flatten

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

No annotations are present, so the description must carry the full burden. It only states the basic operation but omits behavioral traits like side effects, input validation, nesting handling, or return format.

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, which is concise and front-loaded. It could benefit from additional structure like bullet points, but it efficiently communicates the core action.

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?

Despite the tool's simplicity, the description lacks completeness. It does not address input format, nesting behavior, or how it differs from similar tools like transform_flatten, leaving gaps for an agent.

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 has one required parameter 'data' of type string with 0% description coverage. The description does not explain the parameter meaning or expected format (e.g., JSON array).

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 flattens a list of lists into a single list, providing a specific verb and resource. It distinguishes from siblings like map_reduce_mr_map and map_reduce_mr_reduce but lacks depth detail (e.g., one level only).

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?

No usage guidelines are provided. There is no indication of when to use this tool over alternatives like transform_flatten, nor any context on prerequisites or scenarios.

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