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CMU Delphi — CDC ILINet Flu Surveillance

delphi.flu.fluview
Read-onlyIdempotent

Retrieve weekly CDC ILINet influenza-like illness (ILI) surveillance data by US region. Covers national ("nat"), HHS regions (hhs1-hhs10), Census regions (cen1-cen9), and individual states. Returns weighted ILI (wILI) rate, unweighted ILI rate, patient counts, provider counts, and age-group breakdown (0-4, 5-24, 25-49, 50-64, 65+) for each epiweek. Historical data from 1997 onward. No auth — CMU Delphi open epidemiological data, unlimited free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issuesNoFilter to a specific issue/release epiweek (YYYYWW). Omit to get the most recent revision for each epiweek.
regionsYesComma-separated region codes: "nat" (national), "hhs1"-"hhs10" (HHS regions), "cen1"-"cen9" (Census regions), or 2-letter state abbreviation (e.g. "ca"). Multiple: "nat,hhs1".
epiweeksYesEpiweek(s) in YYYYWW format. Single: "202001". Range: "202001-202020". List: "202001,202010,202020". Epiweeks start Sunday; week 1 contains Jan 1.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true. The description adds value beyond these by disclosing 'No auth — CMU Delphi open epidemiological data, unlimited free' and detailing the returned fields (wILI rate, patient/provider counts, age-group breakdown). It does not contradict any annotation.

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 front-loaded with scope and each sentence earns its place: coverage, return fields, historical depth, and auth. It is slightly longer than minimal but every clause contributes information for a fairly complex epidemiological tool.

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

Completeness4/5

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

For a tool with a rich output schema, 100% param coverage, and strong annotations, the description covers data content, output fields, time span, and auth status. The only minor gap is elaboration on the unusual 'issues' (release/epiweek) semantics, but the schema already documents that parameter.

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?

Schema description coverage is 100%, so the baseline is 3. The description repeats the region code vocabulary already present in the schema and adds 'Historical data from 1997 onward' for epiweeks, but it does not add meaningful format or semantic detail beyond what the schema documents.

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

Purpose5/5

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

The description states a specific verb+resource — 'Retrieve weekly CDC ILINet influenza-like illness (ILI) surveillance data by US region' — and enumerates the exact geographic scopes (nat, hhs1-hhs10, cen1-cen9, states). This clearly distinguishes it from the sibling delphi.flu.flusurv (FluSurv-NET hospitalization surveillance) and disease.influenza.cdc, so an agent can tell them apart without opening schemas.

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

Usage Guidelines3/5

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

The description gives clear context on what data it covers (regions, fields, time span) but includes no explicit when-to-use/when-not-to-use guidance or naming of alternatives. With closely related siblings like delphi.flu.flusurv present, explicit routing would help but is not provided.

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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