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AlpineDataWorks Intelligence Server

US Water Stress (Major Basin)

adw.adw_132
Read-only

Returns a 0-100 US water-stress index for major river basins (weekly USGS streamflow vs. normal across a 10-gauge sample, z-scored composite, history since 1975) with score, trend, percentile, top_drivers gauges, and source_lineage. Call when the user asks about drought, streamflow, river basin conditions, water supply, or irrigation risk, or when timing exposure to water-intensive crops (corn, cotton, rice forward contracts) ahead of USDA crop-progress reports. 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

A4.3/5.0
Behavior5/5

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

ReadOnlyHint already signals safety, and the description adds substantive context: the measurement methodology (USGS streamflow vs. normal, 10-gauge sample, z-scored composite), data history since 1975, weekly updates, and the return fields. It also explains the days parameter behavior and the Gold tier requirement, providing transparency beyond annotations.

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 followed by a short update note. It packs essential details without fluff. Slightly more structure (e.g., breaking out use cases) could improve readability, but it remains concise and front-loaded.

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?

Given no output schema, the description does well by listing the output fields and explaining the optional history mode via the schema. It covers methodology, geographic scope, update frequency, and use cases. It could be more explicit about the default return format (current snapshot vs. series) but is otherwise complete.

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 only parameter 'days' has a full description). The tool description does not elaborate on the parameter syntax or semantics beyond what the schema already provides, so a baseline score 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 clearly states it returns a 0-100 US water-stress index for major river basins, listing specific output fields (score, trend, percentile, top_drivers, source_lineage). The title and description align, and the use cases (drought, streamflow, water supply) distinguish it from unrelated sibling tools like health or cancer risk.

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 explicitly states when to call: when the user asks about drought, streamflow, river basin conditions, water supply, or irrigation risk, or for agricultural timing. It does not provide exclusions or mention alternative tools by name, but the guidance is clear and actionable.

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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