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AlpineDataWorks Intelligence Server

by com.alpinedataworks

US Mortgage Complaint Stress

adw.adw_601
Read-only

Returns a 0-100 US mortgage complaint stress score (rolling 90-day CFPB mortgage-complaint count scored against 8 trailing 90-day windows, a 2-year baseline; daily, history to 2011) with trend, z_score, recent_window_count, baseline_window_mean/std, and per-window counts. Call when the user asks about mortgage borrower distress, servicing friction, CFPB complaint trends, or housing-credit stress, or when timing delinquency forecasts, loss-mitigation staffing, or mortgage-credit risk positioning. 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 indicates safety, and the description adds meaningful context: computation method, baseline windows, history to 2011, daily update cadence, and the Gold-tier requirement for history data. This exceeds the annotation baseline and discloses important behavior not visible in structured fields.

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?

Two dense sentences cover definition, methodology, use cases, update frequency, and parameter caveat with no filler. The content is front-loaded and every clause carries useful information.

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?

Even without an output schema, the description enumerates the returned fields (trend, z_score, recent_window_count, baseline stats, per-window counts), explains the 0-100 scale, data history, daily updates, and the optional parameter's behavior. Combined with the schema, it gives an agent sufficient context to invoke and interpret results.

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%, and the single optional 'days' parameter has a thorough description in the schema. The tool description echoes the Gold-tier caveat and history behavior but adds no new semantics beyond the schema, so the 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 opens with a strong verb ('Returns') and precisely identifies the resource (US mortgage complaint stress score), its scale (0-100), methodology (90-day CFPB count vs 8 trailing windows), and date range. This clearly distinguishes it from the many sibling tools by naming the specific domain and metric.

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?

Explicitly lists user intents that should trigger this tool: mortgage borrower distress, servicing friction, CFPB complaint trends, housing-credit stress, and timing delinquency forecasts. It does not mention when not to use it or name alternatives, so it falls short of a perfect 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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