get_health_report

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

No annotations are provided, and the description does not disclose behavioral traits such as whether the tool is read-only, what side effects (if any) exist, or any authentication or rate limit requirements. For a diagnostic tool, the lack of read-only assurance is a gap.

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 a single sentence that front-loads the purpose and enumerates key elements without redundancy. Every word is purposeful and contributes to understanding.

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?

No output schema is provided, and the description does not explain the return format (e.g., counts, detailed lists, or summaries). For a tool with no parameters, the output description is critical but missing.

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 no parameters, so schema coverage is effectively 100%. The description adds meaning by listing the diagnostic categories (orphans, stale facts, etc.), which provides semantic context beyond the empty schema.

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 it provides 'Memory health diagnostics' and enumerates specific aspects (orphans, stale facts, contradictions, decay candidates, DB sizes). However, it does not explicitly differentiate from nearby sibling tools like 'find_contradictions' or 'get_compaction_audit' which overlap in scope.

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?

No guidance on when to use this tool versus alternatives such as 'find_contradictions' or 'get_compaction_audit'. The agent is left to infer use cases from the description alone, which is insufficient for correct tool selection.

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