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

Annotations already indicate read-only and closed-world, and the description adds that answers are evidence-based with citations and that the knowledge base is a 200-chunk dataset. This gives useful behavioral context beyond what the annotations provide, with no contradictions.

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, dense sentence that front-loads the purpose and lists the covered topics. It is concise and structured, though the long enumeration makes it slightly heavy, so it doesn't earn a 5.

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?

There is no output schema, but the description discloses the return type (evidence-based answer with citations) and the knowledge base scope. It doesn't mention the effect of the pillar parameter on results, but for a query tool with good annotations, it is fairly complete.

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 description coverage is 0%, and the description does not mention any parameters. It doesn't explain the pillar filter or max_results, so it fails to compensate for the lack of schema descriptions. The enum values are self-explanatory, but the description adds no value for 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 the tool answers lifestyle medicine questions and specifies the knowledge base topics, distinguishing it from specialized siblings like interpret_labs and drug_safety by its broad scope. However, it doesn't explicitly name alternatives, so it stops short of a perfect score.

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 general lifestyle medicine queries by listing the broad range of topics, but it doesn't provide explicit guidance on when to use this tool instead of the specialized siblings. There are no exclusion criteria or alternative recommendations, so it only meets the 'implied usage' bar.

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