list_predictions

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

With no annotations, the description carries the burden of disclosing behavior. It reveals sorting order (newest first) and optional filtering, but omits details like pagination, result limits, or read-only nature. Adequate but not comprehensive.

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 succinct sentences that immediately convey the main purpose and option. No wasted words; important information is front-loaded.

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 (one optional parameter, output schema exists), the description covers the core functionality, sorting, and provides an alternative. It lacks mention of pagination or result structure, but these are partially covered by the output schema.

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 only parameter, project_id, has 0% schema description coverage. The description adds that it is optional and filters, but does not specify format, constraints, or default behavior. Minimal added value beyond the schema structure.

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 lists predictions sorted newest first, with optional filtering by project_id. It distinguishes itself from get_prediction by noting that tool provides full results and download URL.

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 explicitly suggests using get_prediction(id) for more detailed results, offering a clear alternative. However, it does not provide guidance on when to use list_predictions vs other sibling tools or when filtering is beneficial.

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