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AlpineDataWorks Intelligence Server

US Treasury Fiscal Pulse

adw.adw_573
Read-only

Returns a 0-100 US fiscal-stress score (YoY growth of total public debt from Treasury Debt to the Penny, adjusted for the trend in the average interest rate on the debt) with total_debt, debt_yoy, change_30d, interest_rate_trend, and 12-month history. Call when the user asks about federal debt growth, fiscal sustainability, deficits, or the US interest burden, or when timing duration, Treasury-supply, or fixed-vs-floating funding decisions. Updates: quarterly.

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?

The annotations already declare readOnlyHint=true, so the description need not repeat safety info. It adds useful context: 'Updates: quarterly' and reveals the scoring methodology (YoY debt growth adjusted for interest rate trend). It also lists output fields, giving a clear behavioral picture without contradicting annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is packed with information in two sentences: what it returns, the fields, and when to use it. It is front-loaded with the primary output. Though it is a dense single sentence, every part is relevant and there is no waste.

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

Completeness4/5

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

For a simple read-only tool with one optional parameter, the description covers the main return fields, the score's meaning, and appropriate use cases. It lacks an output schema, but the description lists the fields and history. The only minor gap is not explaining the interaction between the default snapshot and the 'days' parameter, but the schema covers that.

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 covers the only parameter 'days' with a full description, meeting 100% schema coverage. The tool description adds no parameter information, but the schema does the heavy lifting, so a baseline score 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 clearly states the tool returns a specific 0-100 fiscal-stress score, lists the exact fields included (total_debt, debt_yoy, change_30d, interest_rate_trend, 12-month history), and explains the formula. It is precise about the resource (US Treasury fiscal stress) and the action (returns a score), making it unambiguous and distinct from generic siblings.

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 tells when to use it: 'Call when the user asks about federal debt growth, fiscal sustainability, deficits, or the US interest burden...' This is strong when-to-use guidance. However, it does not mention alternatives or when not to use it, so it falls 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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