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AlpineDataWorks Intelligence Server

US Flood-Risk Signal (Gulf Coast)

adw.adw_253
Read-only

Returns a 0-100 US Gulf Coast flood-risk score (scaled peak-vs-current 7-day GloFAS river-discharge ratio via Open-Meteo Flood, daily, 10y history) with flood_risk_score, peak_vs_current, and peak_discharge. Call when the user asks about Gulf Coast flooding, river discharge, rising water levels, or flood exposure, or when timing insurance loss-reserve reviews, property-portfolio risk checks, or underwriting decisions ahead of NWS gauges reaching flood stage. Updates: daily.

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

A4.2/5.0
Behavior4/5

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

The description adds context beyond the readOnlyHint annotation by explaining the data source (Open-Meteo Flood), update frequency ('Updates: daily'), history depth ('10y history'), and the output fields. It does not contradict any annotation and adds meaningful behavioral detail.

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

Conciseness5/5

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

The description is two sentences: the first explains functionality and output, the second gives explicit usage guidance and update frequency. Every clause earns its place with no redundancy, and it is front-loaded with the primary purpose.

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 no output schema, the description compensates by listing the returned fields (flood_risk_score, peak_vs_current, peak_discharge) and explaining the underlying metric. The only minor gap is the lack of explicit units for peak_discharge, but the scale and meaning of the score are clearly stated.

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 the single optional 'days' parameter is well documented in the schema. The description adds no additional parameter-level detail, only indirectly implying the history feature via '10y history' and 'daily' updates. This meets the baseline for full schema coverage but adds no extra value.

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 clearly states the tool returns a 0-100 US Gulf Coast flood-risk score, with a specific calculation method (scaled peak-vs-current 7-day GloFAS river-discharge ratio) and named output fields. This specific verb+resource+scope distinguishes it from the many numbered sibling 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?

The description gives explicit usage triggers: 'Call when the user asks about Gulf Coast flooding, river discharge, rising water levels, or flood exposure' and also lists use cases like insurance loss-reserve reviews and underwriting decisions. It does not mention when not to use it or name alternatives, 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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