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AlpineDataWorks Intelligence Server

Seismic History Index

adw.adw_521
Read-only

Returns a 0-100 seismic history score for any of 3,222 US counties (normalized from the historical earthquake record — frequency and magnitude of past events) with score, percentile, county_fips, county_name, state, as_of, and methodology_version. Call when the user asks about local earthquake history, seismic exposure, or county risk rankings, or when timing site selection, underwriting, or retrofit-budget 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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description adds value by explaining the data source (historical earthquake record), normalization from frequency and magnitude, and the update cadence. No contradictory or misleading behavior is disclosed.

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 concise: one sentence front-loads the purpose and output fields, a second gives usage triggers, and a final phrase covers update frequency. Every sentence carries necessary information without fluff.

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

Completeness5/5

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

Given the simple parameter set, high schema coverage, and read-only annotation, the description provides complete context: purpose, output fields, usage triggers, and freshness. No output schema exists, but return fields are explicitly enumerated, so nothing critical is missing.

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 input schema covers the only parameter 'days' at 100% with a detailed description including range, purpose, and tier requirement. The tool description adds no additional parameter semantics, 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 seismic history score for 3,222 US counties, listing specific output fields (score, percentile, fips, state, etc.) and the normalization basis. This specific verb+resource+scope distinguishes it from sibling risk indices like health or obesity 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?

Explicitly enumerates when to call: when the user asks about local earthquake history, seismic exposure, county risk rankings, or for site selection, underwriting, and retrofit-budget decisions. It lacks explicit when-not or alternative tool names, 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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