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AlpineDataWorks Intelligence Server

Health & Safety MVP Package

adw.adw_p15
Read-only

Returns a 0-100 health-and-safety risk profile for a US county (composite of 7 AlpineDataWorks V2 place-intelligence layers joined on county_fips, refreshed at each source's cadence) with composite_score, component_scores, drivers, and coverage. Call when the user asks about a location's health and safety risk, local hazards, or community health conditions, or when timing site selection, underwriting, relocation, or expansion decisions. Updates: on source cadence.

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 declare readOnlyHint=true, so the description doesn't need to restate safety. It adds valuable context about refresh cadence ('refreshed at each source's cadence') and output structure ('composite_score, component_scores, drivers, and coverage'), enriching the agent's understanding 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.

Conciseness5/5

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

Three succinct sentences: the first states the core function, the second gives clear usage triggers, and the third notes update frequency. No fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description lists return fields and composite nature, it fails to explain how the target county is specified — the input schema contains no county_fips parameter. It also omits interpretation of the 0-100 scale and 'drivers'/'coverage' fields, which matters since no output schema exists.

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?

The only parameter (days) is fully documented in the schema with range, optionality, and Gold tier requirement (100% coverage). The description adds no additional parameter-specific guidance, 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 opens with a specific verb and deliverable: 'Returns a 0-100 health-and-safety risk profile for a US county'. It also distinguishes itself from sibling single-layer tools (e.g., air_quality_risk, county_cancer) by clarifying it is a 'composite of 7 AlpineDataWorks V2 place-intelligence layers'.

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 provides explicit 'Call when...' scenarios covering location risk, hazards, community health, and business decisions like site selection and underwriting. It lacks when-not-to-use guidance or named alternative tools, so it doesn't reach 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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