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AlpineDataWorks Intelligence Server

by com.alpinedataworks

Healthcare Cost Inflation Index

adw.adw_040
Read-only

Returns a 0-100 healthcare cost inflation index (monthly FRED medical CPI vs core CPI year-over-year spread, z-scored over a 36-month window) with score, trend, confidence, medical_cpi_yoy_pct, core_cpi_yoy_pct, healthcare_spread_pct, and top drivers. Call when the user asks about healthcare inflation, medical cost trends, or health costs versus core inflation, or when timing employer health-plan renewals, premium and benefits renegotiation, or healthcare budgeting. Updates: monthly.

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 annotations already indicate readOnlyHint=true and openWorldHint=false. The description adds useful behavioral context: monthly updates, the 36-month z-score window, and the data sources. It does not contradict annotations and provides meaningful methodology details beyond the safety profile.

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 well-structured sentences: the first defines the index and outputs, the second provides use cases and update frequency. Every sentence is informative with no wasted words.

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?

The description lists all return fields and covers use cases, update frequency, and methodology, which is sufficient given no output schema. It does not explain the confidence metric or top drivers in detail, but the essential information for invoking the tool is present.

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 description coverage is 100%, and the schema fully explains the single 'days' parameter, including the optional history behavior and Gold tier requirement. The main description adds no extra parameter information, so the baseline 3 applies.

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 healthcare cost inflation index with a precise definition (monthly FRED medical CPI vs core CPI spread, z-scored over 36 months) and enumerates the output fields. It is specific and distinguishes this tool from siblings by focusing on healthcare inflation.

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 explicitly lists when to call the tool, including specific query topics and business scenarios like employer health-plan renewals and healthcare budgeting. However, it does not mention when not to use it or alternative tools, so it lacks exclusions.

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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