health_check

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

No annotations, but description reveals read-only nature (health check) and lists returned data. Lacks explicit safety or side-effect info, but adequate for a simple query.

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 sentences: first states purpose and outputs, second gives usage scenario. No fluff, front-loaded with critical info.

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 parameterless health check without output schema, description covers purpose, outputs, and usage. Completeness is sufficient given simplicity.

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?

No parameters exist, so schema coverage is 100%. Baseline score of 4 applies as description adds no parameter details by necessity.

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 specifies the tool checks backend health and shows plugins, cache stats, version. Distinct from sibling tools like check_code or fix_issue.

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?

States explicit use case: 'diagnose when analysis isn't working as expected.' Provides clear context without needing exclusions for a health check.

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