atlas_auto_findings_queue

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

No annotations provided, so the description carries the full burden. It mentions 'auto-generated' and 'for human review' implying read-only, but lacks details on whether data is mutable, access restrictions, or that the tool returns a collection (likely all cards) with no parameters.

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?

Single sentence that is front-loaded with the core purpose. Efficient and to the point, though slightly more structure (e.g., listing fields separately) could improve readability.

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 simple tool with no parameters, the description is minimally adequate. It mentions output fields but does not elaborate on return shape, ordering, or potential limitations (e.g., no pagination). With no output schema, more detail would be beneficial.

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?

Input schema has zero parameters (100% coverage), so there is nothing to describe. The description compensates by explaining the output content (fields like country, mechanism, evidence, confidence), providing value beyond the schema.

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 returns auto-generated draft findings ('cards') surfaced for human review, mentioning key fields (country, mechanism, evidence, confidence). While it distinguishes from siblings by specifying 'under-reported incidents', it could be more precise in naming the exact resource type.

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 explicit guidance on when to use this tool versus alternatives. The description implies usage by journalists for under-reported incidents but does not mention exclusions or comparisons to similar sibling tools like 'atlas_auto_incidents_pending'.

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