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Health Fluview Influenza Cdc

health_fluview_influenza_cdc
Read-only

CDC FluView weekly influenza-like illness (ILI) and weighted ILI for the US or a region (served via Delphi Epidata, which mirrors CDC FluView): epiweek, ILI %, weighted ILI %, patient and provider counts. Give an epiweek range of up to 12 weeks. No outbreak maps. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
regionYes'nat' for US national, or a state code like 'vt' (lowercase letters, 2 to 5 characters)
epiweekToYesLast epiweek, YYYYWW, at most 12 weeks after the first
epiweekFromYesFirst epiweek, YYYYWW, e.g. 202440

Output Schema

NameRequiredDescriptionDefault
toNo
fromNo
weeksNo
regionNo
sourceNo
checkedAtNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already mark this read-only and open-world, and the description goes well beyond them: it discloses metered pricing ($0.002 USDC per successful call via x402 on Base/Solana/Arc) and, crucially, that failed calls are not charged — decisive information for an agent weighing call cost. It also bounds the query window to 12 weeks.

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?

Purpose and scope are front-loaded in the first clause, and the pricing caveat is appended as a single efficient sentence. The parenthetical about Delphi Epidata is slightly parenthetical-heavy but earns its place by establishing provenance/mirroring.

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?

With an output schema present, return values needn't be spelled out, yet the description still enumerates them. Combined with region/range rules and cost behavior, an agent has what it needs to call correctly; only edge cases (invalid epiweek handling, error responses) are left unstated.

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 coverage is 100%, and all three parameters carry their own descriptions ('nat' or 2-5 letter state code, YYYYWW format, 12-week span), so the schema already does the heavy lifting. The description restates the 12-week range limit but adds no format or semantics beyond the schema; baseline 3 is appropriate.

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 names a specific verb ('weekly ILI and weighted ILI') and a specific resource/dataset ('CDC FluView', served via Delphi Epidata), plus the exact fields returned (epiweek, ILI %, weighted ILI %, patient/provider counts). No sibling in the list covers FluView ILI data, so an agent can route here unambiguously.

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

Usage Guidelines4/5

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

It gives the operative constraint ('Give an epiweek range of up to 12 weeks') and a scope exclusion ('No outbreak maps'), which is meaningful for an agent deciding whether this tool fits. It stops short of naming an alternative tool for outbreak maps or for non-epiweek resolutions, so it is clear context rather than full when/when-not guidance.

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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