fleet_health

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

Annotations already declare the tool as read-only and non-destructive. The description adds behavioral context beyond annotations by explaining that workers reports every heartbeat-publishing process and that stranded is true only when pending work exists without a live runner. This clarifies the semantics of the reported data without contradicting annotations.

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 three sentences long, front-loaded with the core purpose, and each sentence adds meaningful value. The concept of stranded tasks is explained once, concisely, without redundancy. It is well-structured and free of 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?

With no output schema, the description adequately communicates what the tool returns conceptually: queue counts, worker heartbeats, and a stranded flag. It covers the essential semantics an agent needs to interpret results, though it does not specify exact response fields or error conditions. For a simple one-parameter health check, this is sufficient.

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 input schema has 0% description coverage for the single parameter app_id, and the tool description does not mention app_id at all. While the parameter name is self-explanatory (an application identifier), the description fails to compensate for the schema's lack of detail, leaving the agent to infer the expected value format and scope.

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's purpose: reporting task queue counts by status and live worker heartbeats. It uses specific terminology (pending, stranded, workers) and explains the key distinction between queued and stranded tasks, which sets it apart from sibling tools like fleet_status or integration_status.

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 implies when to use this tool—when you need to understand queue depth in the context of worker liveness and detect stranded tasks—but it does not explicitly name alternatives or provide when-not-to-use guidance. The context is clear enough for an informed agent, but it lacks explicit exclusions or comparisons.

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