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AlpineDataWorks Intelligence Server

Global Food-Insecurity Pulse

adw.adw_417
Read-only

Returns a 0-100 food-insecurity pulse score (population-weighted momentum in insufficient-food-consumption prevalence across 24 WFP HungerMap countries vs each country's trailing 60-90-day baseline) with current and baseline prevalence, z_score, most_affected_adm0_id, and countries_analyzed. Call when the user asks about global hunger trends, food-crisis momentum, or humanitarian conditions, or when timing early-action funding, aid pre-positioning, or ag-commodity risk reviews. 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

A4.1/5.0
Behavior4/5

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

Annotations already mark it read-only, and the description adds meaningful behavioral context: the score is population-weighted momentum vs a 60-90-day baseline, updates daily, and returns specific fields. It also clarifies the scope (24 WFP HungerMap countries) without contradicting 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?

Two sentences of dense, front-loaded information; the first sentence conveys the core function and return fields while the second gives usage context and update cadence. It is slightly complex but every phrase earns its place.

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 read-only single-parameter tool, the description covers the score definition, country scope, baseline window, return fields, update frequency, and usage scenarios. The absence of an output schema is compensated by listing the main return fields. Minor gaps like potential limitations or handling of missing data prevent a 5.

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% with a self-explanatory 'days' parameter, so baseline is 3. The tool description does not mention the optional history feature at all, leaving the schema to carry that meaning; no additional semantic value is added beyond the schema.

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 specific 0-100 food-insecurity pulse score with methodology and return fields. The verb 'Returns' and the resource ('food-insecurity pulse score') make its function unambiguous, and the inclusion of countries and baseline distinguishes it as a specialized global index among many siblings.

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 identifies five use-case triggers: global hunger trends, food-crisis momentum, humanitarian conditions, and timing early-action funding/aid positioning/ag-commodity reviews. However, it does not state when not to use it or name alternative tools, so it falls short of a full 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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