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AlpineDataWorks Intelligence Server

Infectious-Disease Burden

adw.adw_125
Read-only

Returns a 0-100 US infectious-disease burden score (composite z-score of CDC NNDSS notifiable-disease case counts across a multi-disease basket with year-over-year momentum) with IOM top_drivers, source_lineage, and methodology_version. Call when the user asks about notifiable-disease burden, outbreak surveillance, epidemic risk, or CDC case-count trends, or when timing group-health underwriting, actuarial re-pricing, or seasonal-versus-structural disease signals. Updates: weekly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoOptional: return a daily HISTORY series of the last N days (up to 5 years of real archived data) instead of the current snapshot. History requires Gold tier; without it, the current snapshot is returned.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and the description aligns by saying 'Returns'. It adds behavioral context beyond annotations: weekly update frequency, the composite z-score methodology, and the exact returned fields. It doesn't mention authentication or rate limits, but the read-only annotation lowers the bar.

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 dense sentence that front-loads the core result, then adds trigger conditions and update cadence. Every clause carries information, but the sentence is quite long and uses technical jargon. It's efficient, not bloated.

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?

There is no output schema, but the description compensates by listing the key output fields and explaining the nature of the score. Combined with the data source, use cases, and update frequency, it provides enough context for a straightforward read-only API tool.

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%: the single 'days' parameter has a full description covering the optional history behavior, Gold tier restriction, and range. The description adds no additional parameter-specific semantics, so the baseline of 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 uses a specific verb 'Returns' and clearly defines the resource: a 0-100 US infectious-disease burden score based on CDC NNDSS notifiable-disease counts. It also lists the output components (IOM top_drivers, source_lineage, methodology_version), making the tool's purpose unambiguous and distinguishable from generic index tools.

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?

Explicitly provides a trigger list: 'Call when the user asks about notifiable-disease burden, outbreak surveillance, epidemic risk, or CDC case-count trends' and includes practical applications like group-health underwriting and actuarial re-pricing. It lacks explicit alternatives or when-not-to-use guidance, so it stops short of a 5.

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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TDQS

B3.3/5.0
Disambiguation1/5

With 318 tools named adw.adw_###, agents cannot tell them apart without reading full descriptions. Multiple tools cover the same domain (e.g., at least three USD strength scores: adw_055, adw_250, adw_580; four supply-chain stress scores: adw_009, adw_019, adw_020, adw_547), making misselection highly likely.

Naming Consistency3/5

The vast majority follow a consistent numeric ID pattern (adw.adw_###), but a small set breaks this with descriptive snake_case names (adw.catalog, adw.sample, adw.county_cancer, etc.). The numeric IDs are predictable but convey no semantic meaning, mixing with the few named tools and creating moderate inconsistency.

Tool Count1/5

318 tools is far beyond any reasonable scope for an intelligence server; even the largest sophisticated APIs rarely exceed 50. This extreme count suggests poor curation and will overwhelm agents with choice, making efficient tool selection impractical.

Completeness3/5

The server covers an extremely broad range of domains (crypto, macro, supply chain, healthcare, climate, county demographics), and includes discovery tools like adw.catalog and adw.sample. However, the surface is redundant and not systematically complete—many overlapping indices exist while other potentially valuable operations (e.g., raw data export, historical trend queries) are missing, leaving moderate gaps.

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