list_ai_queue

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

No annotations are present, so the description carries the burden. It indicates the output is 'compact summaries' and that starting work is a separate step (start_task), but it doesn't explicitly state read-only behavior, pagination, or included fields. This is adequate but not rich.

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?

Three short clauses, each earning its place: what it lists, what filters exist, and what to do next. The main action is front-loaded and there is no filler.

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 list tool with no required parameters and no output schema, the description covers the core need and the follow-up action. The vague 'compact summaries' is the only gap; it doesn't specify exact return fields, but the workflow is clear.

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 description coverage is 100%, so the baseline is 3. The description only reiterates 'priority and tag filters' without adding new semantics for teamId/projectId or value formats.

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 states a specific verb ("List"), a precise resource ("tasks queued for AI processing"), and the return style ("compact summaries"). It clearly distinguishes this from sibling list_tasks and search_tasks, which operate on the general task set.

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?

It gives clear context: this is the tool to see queued AI work, with optional priority/tag filters, and explicitly points to start_task as the follow-up action. It doesn't name alternatives or exclusions, but the AI-queue scope is evident.

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