Read the estimation rules that NHANES analyses must follow. Avoid invalid results by applying these enforced guidelines before starting your analysis.
Rules for valid NHANES estimation that this server enforces. Read before analyzing.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full burden. It discloses that the tool is read-only (no side effects) and returns rules the server enforces. It does not specify the exact format or content of the rules, but for a reference/documentation tool, this is acceptable. The description adds context beyond the name, which is useful for an agent to know it's a prerequisite.
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 extremely concise and front-loaded: the first sentence states the core purpose, and the second gives an actionable instruction. Every word earns its place. It is appropriately sized for a simple reference tool.
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?
Given the tool's simplicity (no parameters, no complex logic), the description is complete for an agent to know when and why to call it. It mentions the server enforces these rules and that reading is required before analysis, which is sufficient. Some might expect more details about the rules themselves, but the tool's output schema likely contains that, so it is not required here.
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 schema provides no parameter semantics. The description compensates by explaining the tool's purpose as providing rules, which is the only semantic needed. With no parameters, the description adds complete value by clarifying what the tool does, earning a baseline above 3.
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 provides rules for valid NHANES estimation enforced by the server. It uses a specific noun ('rules') and clarifies the context (NHANES estimation). It distinguishes itself from siblings by being a meta-tool about rules rather than a data operation, which is implied but not explicit.
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 explicitly instructs to read before analyzing, which signals when to use it (before data analysis or estimation). It does not explicitly name alternative tools that could serve a similar purpose, but given the unique meta-tool nature, alternatives are not obvious. The 'read before analyzing' is clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.