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AlpineDataWorks Intelligence Server

DoD Contract Obligation

adw.adw_533
Read-only

Returns a 0-100 county defense-spending concentration score (trailing-12-month DoD prime-award obligations by place of performance, percentile-ranked across all US counties) with obligations_12mo_usd, award_count, national_share_pct, rank, and methodology_version. Call when the user asks about DoD spending concentration, defense hub counties, or a region's defense-economy exposure, or when timing facility siting, govcon market entry, or defense-dependent credit reviews. 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 read-only nature is known. The description adds meaningful behavioral context beyond annotations: the trailing-12-month rolling window, percentile-ranking method, output fields, and 'Updates: on source cadence' – indicating data freshness. This goes beyond the bare annotation.

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 a single front-loaded sentence stating the core return value, followed by explicit usage triggers and a brief update note. No wasted words; every clause adds information.

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?

There is no output schema, so the description lists output fields (obligations_12mo_usd, award_count, etc.) which is helpful. However, it is ambiguous whether the tool returns a single score for a specific county or a list for all counties, and there is no county selection parameter. The description does not clarify how the user's geographic focus is resolved, leaving a gap for agent invocation.

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% for the single 'days' parameter, with a thorough explanation including the Gold tier requirement and fallback to current snapshot. The description text itself does not add params information, so baseline 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 begins with a specific verb ('Returns') and a clearly defined resource ('county defense-spending concentration score'), followed by precise methodology (trailing-12-month DoD prime-award obligations, percentile-ranked across US counties) and output fields. This distinguishes the tool from siblings even though sibling names are opaque.

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 DoD spending concentration, defense hub counties, or a region's defense-economy exposure...' It also adds concrete use cases like facility siting and credit reviews. However, it does not mention when not to use it or name alternative tools, falling short of 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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