server_status

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

No annotations are provided, so the description carries the full burden. It discloses that checks report exact fixes and that queue depth and last job are included, which is useful. However, it does not explicitly state whether the operation is read-only, requires specific permissions, or has side effects, which is a gap for a tool with no annotation safety profile.

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 two sentences, front-loaded with the tool's role, followed by a concise list of checks and reports. Every word earns its place without unnecessary elaboration.

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 zero-parameter diagnostic tool with an output schema, the description covers the main functionality and clearly states what will be checked and reported. It does not need to describe return values due to the output schema. A minor gap is the lack of explicit read-only behavior, but it is largely implied.

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 tool has zero parameters, so the input schema is empty. The description adds context about what is validated and reported, which is relevant but not parameter-level detail. With zero parameters, the baseline is 4 per the rubric.

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 identifies the tool as a health check and first-run diagnostic, listing specific validation targets (binary, metallib, weights, weight layout, worker venv) and additional reporting (queue depth, last job). This distinguishes it from sibling tools like generate_model or render_preview, which focus on generation/rendering.

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 usage for setup validation and diagnostics but does not explicitly state when to prefer this over siblings or provide exclusions. It mentions 'first-run diagnostic' which suggests a specific use case, but no clear when-not-to-use guidance is included.

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