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global_stats

View current global flight totals, busiest aircraft types and airlines from volunteer ADS-B data. Note figures undercount regions without receiver coverage.

Instructions

How much is flying right now, worldwide: totals, busiest types and airlines.

A single shared snapshot of everything volunteer receivers can hear. Note this is always an undercount of real global traffic — oceans, Africa and central Asia have little to no receiver coverage, so those aircraft are simply absent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It discloses a key limitation: the data is always an undercount and sparse receiver coverage means oceans, Africa, and central Asia are absent. It also explains it is a single shared snapshot. It does not mention refresh cadence or output format, but the caveat is substantial and useful.

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 short paragraphs with a front-loaded core question, a scope sentence, and a one-sentence caveat. Every sentence earns its place; there is no fluff or repetition.

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?

There is no output schema, so the description's mention of totals, busiest types, and airlines is important and mostly sufficient for an agent to know what to expect. It could add exact output shape or update cadence, but for a parameterless aggregate endpoint the description is adequately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there are no parameter semantics to clarify. The baseline for a no-parameter tool is 4, and the description appropriately focuses on what the returned snapshot represents rather than inventing parameter detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear purpose: showing how much is flying worldwide now, with totals, busiest types, and airlines. It is recognizable as a global aggregate view and implicitly distinguishes from sibling tools like busiest_airports or spotting_stats, though it does not explicitly contrast any sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool: when you want a worldwide current-traffic snapshot. It adds a valuable coverage caveat. However, it never explicitly says when not to use it or names alternatives such as spotting_stats, busiest_airports, or viewing_conditions.

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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