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PopHIVE MCP Server

PopHIVE MCP Server

by Cicatriiz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

compare_states

Compare health metrics across multiple states using datasets like immunizations, respiratory diseases, and chronic conditions. Select metrics and time periods to analyze state-level differences.

Instructions

Compare health metrics across multiple states

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset": "<dataset>",
      "states": "<states>",
      "metric": "<metric>"
    },
    "name": "compare_states"
  }
}

Input Schema

NameRequiredDescriptionDefault
metricYesSpecific metric to compare (e.g., "vaccination_rate", "ed_visits", "positivity_rate")
statesYesArray of state codes or names to compare
datasetYesDataset to analyze
time_periodNoTime period for comparison (e.g., "latest", "2024", "last_6_months")

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removedv1.1.0
  3. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only states that it compares metrics, implying a read operation, but does not disclose what the output looks like, any limitations, or side effects. For a tool with required parameters and no output schema, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no unnecessary words. It effectively communicates the core purpose without redundancy. It could be slightly expanded to include usage guidance without losing conciseness, but given its current length, it earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters (3 required), no output schema, and no annotations, the 6-word description is too minimal. It does not explain what the comparison output is, any constraints beyond schema, or how results are structured. The description leaves significant gaps for an agent trying to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for its 4 parameters. The description adds no additional meaning beyond the schema; it simply echoes the tool's purpose. According to the rubric, with coverage >80%, baseline is 3, and the description does not improve it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Compare health metrics across multiple states' clearly states the verb (compare) and resource (health metrics across states). While it distinguishes from siblings like filter_data and time_series_analysis, it does not explicitly differentiate from search_health_data which could also compare across states. Still, the purpose is well communicated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus siblings like filter_data, get_available_datasets, search_health_data, or time_series_analysis. There is no mention of prerequisites or context that would help an agent choose this tool over others.

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

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