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AlpineDataWorks Intelligence Server

Climate Adaptation Capex

adw.adw_030
Read-only

Returns a 0-100 climate-adaptation capex priority score (geospatial flood, wildfire, and heat hazard data from NOAA NCEI, USGS, and the World Bank, combined with asset location and value into a risk-adjusted ROI per intervention) with score, trend, confidence, and top_drivers. Call when the user asks about physical climate risk, facility resilience, flood or heat exposure, or adaptation ROI, or when timing capital allocation across climate-resilience projects. 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

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds meaningful behavioral details: daily updates, data source provenance (NOAA NCEI, USGS, World Bank), and output composition. It does not disclose rate limits or error conditions, but the read-only safety profile is covered by annotations, so a 4 is appropriate.

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 a single substantive sentence plus a brief usage instruction and update frequency. It front-loads the return value and packs in essential context (data sources, output fields) without waste, though the parenthetical list makes it somewhat dense.

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 tool with one optional parameter and no output schema, the description is complete: it explains what is returned, when to use it, data sources, update cadence, and the optional history behavior is fully documented in the schema. No critical use-case or output information 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?

The only parameter 'days' has 100% schema description coverage, including its optional nature, history mode, and Gold tier requirement. The main description does not mention the parameter, but the schema fully explains it, so the baseline of 3 is appropriate with no added value needed.

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') and a well-defined resource ('0-100 climate-adaptation capex priority score'), plus lists output fields (score, trend, confidence, top_drivers) and data sources. It clearly distinguishes this tool from generic siblings by domain and use case, and the 'Call when' section reinforces purpose.

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?

Explicit 'Call when' guidance is provided for physical climate risk, facility resilience, flood/heat exposure, adaptation ROI, and capital allocation timing. It lacks explicit statements of when NOT to use or named alternative tools, so it falls just 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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