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AlpineDataWorks Intelligence Server

US Federal Monthly Budget Deficit Stress

adw.adw_392
Read-only

Returns a 0-100 US federal budget deficit stress score (monthly federal receipts vs. outlays, z-scored against 45.8 years of history since FY1981) with stress_score, revenue_trend, spending_trend, historical_percentile, confidence, and methodology_version. Call when the user asks about the federal deficit, fiscal stress, tax-revenue erosion, Treasury borrowing needs, or shutdown risk, or when timing duration, auction-supply, or government-contract exposure decisions. 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

A4.7/5.0
Behavior5/5

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

The description discloses methodology (z-scored history since FY1981), update frequency (monthly), and the Gold-tier requirement for the `days` parameter (the description explicitly states that without Gold tier, the current snapshot is returned). This adds value beyond the readOnlyHint annotation, which already signals a safe read operation.

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 sentences long, front-loaded with the core purpose, followed by when-to-use guidance and update frequency. Every sentence carries useful information without redundancy or 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?

Despite having no output schema, the description enumerates the return fields (stress_score, revenue_trend, spending_trend, historical_percentile, confidence, methodology_version). It also explains the scoring basis, update cadence, and parameter behavior, making the tool well-suited for an agent to decide and invoke 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 schema description covers the `days` parameter fully (optional, returns history, requires Gold tier, falls back to snapshot). The tool description does not add any extra parameter-specific meaning beyond what the schema already provides. With 100% schema coverage, the baseline of 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 uses a specific verb ('Returns a 0-100 US federal budget deficit stress score') and clearly states the resource and methodology (monthly federal receipts vs. outlays, z-scored against 45.8 years of history). It also lists the exact output fields, making the tool's purpose unambiguous and distinct from the many sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit trigger conditions: 'Call when the user asks about the federal deficit, fiscal stress, tax-revenue erosion, Treasury borrowing needs, or shutdown risk, or when timing duration, auction-supply, or government-contract exposure decisions.' This gives clear guidance on when to invoke this tool, though it doesn't mention alternative tools by name.

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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