queue_active

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

With no annotations, the description carries full burden. It discloses that the tool filters to genuinely in-flight tasks by default, adds a meta.all_done field, and that include_finished reveals just-completed tasks with their status. While it doesn't cover error handling or edge cases, it sufficiently explains the core behavior for an AI agent.

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 compact yet informative. It front-loads the core purpose, then provides necessary context about the raw endpoint's ambiguity, then details the default behavior and parameter usage. Every sentence contributes meaning without redundancy.

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 tool with a single optional parameter and no output schema, the description is remarkably complete. It explains the default filtering, the meta.all_done field for looping, and how to retrieve finished statuses. An agent has sufficient information to use the tool correctly in a polling loop.

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%, so baseline is 3. The description adds value by explaining when to set include_finished:true—specifically to see if an async op succeeded or failed. This context goes beyond the schema's literal description and helps an agent decide parameter usage.

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 polls FastPanel background tasks and provides a deterministic done/not-done signal. It distinguishes itself from the raw /api/queue endpoint by filtering to in-flight tasks and adding the meta.all_done field. This specificity makes the purpose unambiguous.

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 explains when to use this tool (polling for completion) and when not (naive polling of raw endpoint). It also gives guidance on the include_finished parameter: set to true to check whether an async op succeeded or failed. This provides clear context for selecting the tool over alternatives.

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