sentinel_active_learning_queue

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

The description explains the ranking criterion (distance from decision threshold) and the linkage to report_miss. Without annotations, it lacks explicit statements about side effects (e.g., whether listing is read-only) or whether draining modifies state. The description is 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 concise sentences with no redundancy. Every word adds value.

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?

No output schema is provided, and the description does not specify the return format or structure of each forecast item. The agent lacks information about what fields are available (e.g., forecast value, threshold distance, item ID) to process the queue effectively.

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?

Schema coverage is 100% and the description restates the schema's parameter description ('Optional ISO country code filter'). No additional meaning beyond what the schema provides.

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 that the tool returns an uncertainty-sampled queue of forecasts ranked by distance from decision threshold. It uses specific terms like 'forecasts' and 'decision threshold', and the name includes 'active_learning'. However, it does not explicitly differentiate from similar sibling tools like atlas_auto_findings_queue.

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 mentions that each item links to /v1/sentinel/report_miss for draining the queue, implying a workflow. However, it does not specify when to use this tool over alternatives, nor does it provide exclusions or prerequisites.

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