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AlpineDataWorks Intelligence Server

by com.alpinedataworks

Foreign-Entity Lobbying Index

adw.adw_430
Read-only

Returns a 0-100 foreign-entity lobbying index (z-score of new FARA registrations over the trailing 90 days against a 12-quarter DOJ baseline) with foreign_lobbying_score, z_score, recent_90d_new_registrations, baseline_90d_mean/std, active_registrant_stock, and top_registrant_state_recent. Call when the user asks about foreign influence, FARA activity, or foreign-government lobbying intensity, or when timing policy-risk hedges, government-affairs spend, or compliance business development. 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?

Annotations already declare readOnlyHint=true, so the safe-read behavior is covered. The description adds meaningful context beyond annotations by detailing the calculation method (z-score against a 12-quarter baseline), update cadence ('Updates: daily'), and the returned fields, which helps an agent understand the nature and freshness of the data.

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 dense but every sentence contributes: output definition, returned fields, use cases, and update cadence. It is front-loaded with the most important information and contains no filler or redundancy.

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?

For a single-parameter, read-only tool with no output schema, the description is thorough: it specifies the index scale, computation, output fields, relevant use cases, and update frequency. The optional history behavior is covered in the input schema, so no significant context 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?

Schema coverage is 100% for the single optional 'days' parameter, and the schema description already explains the history behavior and Gold tier restriction. The tool description does not need to repeat parameter details; it adds value through output field names rather than parameter semantics.

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 ('Returns') and a concrete resource ('0-100 foreign-entity lobbying index'), including the exact formula and output fields. It clearly distinguishes this tool from the many opaque sibling tools by naming FARA registrations, DOJ baseline, and the index components.

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 'Call when' with concrete triggers (foreign influence, FARA activity, policy-risk hedging, etc.), giving strong contextual guidance. It does not provide exclusions or name specific sibling alternatives, but the use-case list is sufficiently clear for an agent to select this tool.

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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