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AlpineDataWorks Intelligence Server

Seismic-Risk Pulse

adw.adw_129
Read-only

Returns a 0-100 global seismic-activity index (daily composite z-score of USGS M4.5+ earthquake energy, event count, and shallow-focus share; 10.5-year history) with score, percentile, trend, top_drivers, and source_lineage. Call when the user asks about earthquake activity, seismic risk, tremors, or geophysical hazards worldwide, or when timing disruption alerts for ports, pipelines, mines, or insured assets near active epicenters. 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

A4.3/5.0
Behavior4/5

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

The readOnlyHint annotation already signals a safe read operation. The description adds useful behavioral context: daily update cadence, the index's component breakdown, 10.5-year history, and the output fields (score, percentile, trend, top_drivers, source_lineage). This goes beyond the annotations without contradicting them.

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 concise sentences: the first states what is returned and its key properties, the second gives usage context and update frequency. No wasted words; front-loaded with the core purpose.

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?

With no output schema, the description adequately lists the return fields (score, percentile, trend, top_drivers, source_lineage) and explains the data source and update frequency. Combined with the schema's description of the optional parameter, an agent has enough context to select and invoke the tool correctly.

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 described in the schema (optional, history length, tier requirement). The description does not add parameter-specific semantics beyond what the schema already provides, so the high schema coverage baseline of 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 identifies the tool as returning a 0-100 global seismic-activity index with specific composition (z-score of USGS M4.5+ earthquake energy, event count, shallow-focus share) and history length. This distinguishes it from sibling tools in other domains (e.g., health_risk, air_quality_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?

The description explicitly states when to call the tool: 'Call when the user asks about earthquake activity, seismic risk, tremors, or geophysical hazards worldwide, or when timing disruption alerts...' This provides clear context, though it does not mention when not to use it or suggest alternatives.

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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