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AlpineDataWorks Intelligence Server

US Significant-Rulemaking Velocity

adw.adw_614
Read-only

Returns a 0-100 US significant-rulemaking velocity score (90-day count of economically significant EO 12866 rules plus proposed rules in the Federal Register, vs 8 trailing windows) with trend, z_score, recent_window_count, baseline_window_mean, and per-variant counts. Call when the user asks about regulatory acceleration, federal rulemaking pace, or the compliance-cost pipeline, or when timing compliance staffing, comment-period capacity, or policy-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?

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds valuable behavioral context: updates daily, the score's composition, and the specific output fields (trend, z_score, etc.). This goes beyond what annotations provide, though it doesn't disclose edge cases or return formatting details.

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 sentences: the first packs the core function and output fields, the second lists use cases. No filler, no repetition, and the most important information is front-loaded. Every sentence earns its place.

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 zero-required-parameter tool with no output schema, the description is complete: it explains the metric, the return fields, the update frequency, and the contexts in which to use it. The optional 'days' parameter is fully documented in the schema, so nothing 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 description coverage is 100% (the 'days' parameter is fully explained with bounds and tier requirements). The tool description itself does not mention the parameter, but since the schema carries the full burden, 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 opens with 'Returns a 0-100 US significant-rulemaking velocity score' and defines the exact computation (90-day count of economically significant EO 12866 rules plus proposed rules in the Federal Register, vs 8 trailing windows). This is a specific verb+resource with a clear scope and distinct metric, easily differentiated from any sibling tool.

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 lists when to call it: 'Call when the user asks about regulatory acceleration, federal rulemaking pace, or the compliance-cost pipeline, or when timing compliance staffing, comment-period capacity, or policy-risk positioning.' This provides clear context but does not mention alternatives or exclusions, which would push it to 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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