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AlpineDataWorks Intelligence Server

Airspace Concentration Index

adw.adw_546
Read-only

Returns a 0-100 airspace concentration index (live Herfindahl over tracked aircraft counts by country from the OpenSky ADS-B network, hourly refresh) with country leaderboard shares, altitude distribution, and tracked/airborne/ground totals. Call when the user asks how concentrated global air traffic is right now, which countries dominate live flights, or whether an airspace disruption is visible, or when timing cargo rerouting, travel-risk escalations, or aviation-exposure decisions. Updates: hourly.

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?

Beyond the readOnlyHint annotation, the description adds valuable behavioral context: update frequency ('hourly refresh'), data source ('OpenSky ADS-B network'), output structure ('country leaderboard shares, altitude distribution, and tracked/airborne/ground totals'), and the Gold tier requirement for the 'days' history parameter. It does not mention rate limits or permission details, but those are less critical given the read-only nature.

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 two sentences, front-loaded with the core functionality and followed by use cases. It is generally concise, but there is slight redundancy: 'hourly refresh' in the first sentence and 'Updates: hourly' at the end. This minor duplication prevents a perfect score.

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?

Given there is no output schema, the description compensates well by enumerating return components (index, leaderboard shares, altitude distribution, totals) and use cases. It also explains update cadence and data source. The optional parameter behavior is covered in the schema. Overall, the description is complete enough for an agent to select and invoke the tool 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?

Schema description coverage is 100%: the single 'days' parameter is fully documented in the input schema, including range, optionality, and Gold tier requirement. The tool description itself does not mention the parameter, but since the schema does the heavy lifting, 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 clearly states a specific verb ('Returns') and resource ('airspace concentration index'), with detailed components (0-100 index, Herfindahl over tracked aircraft counts, leaderboard shares, altitude distribution, totals). It distinguishes itself from siblings by focusing on live global air traffic concentration, and even lists use cases for when it should be called.

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 provides explicit 'Call when' scenarios (e.g., 'how concentrated global air traffic is right now', 'which countries dominate live flights', 'whether an airspace disruption is visible'), which is strong usage guidance. However, it does not mention any alternatives or when NOT to use this tool, 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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