aircraft_density

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

While there are no formal annotations, the description effectively communicates the complexity of the data returned—it is not just a simple count but a structured grid of multiple data points (category, degradation, vessel count). This helps the agent understand the richness of the expected output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise, using two sentences to cover the definition of the output product and the methodology for specifying the input area. The structure is logical and immediately useful for decision-making.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is very complete in defining the *nature* of the data being returned, which is often more important than parameter-level detail when dealing with structured grid outputs. It provides sufficient context on the result format and required input types.

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

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

Since schema description coverage is 0%, the description must carry the full burden. It adds critical conceptual context by defining the two primary input modes (center vs. bbox) and stating that 'cell_deg sets grid resolution,' which helps the agent understand the function of those parameters.

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

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

The tool clearly defines its purpose as calculating 'aircraft density' and specifies the highly granular output structure (grid of cells with count, category, GNSS-degraded data, totals, and peak cells), making it distinct from general location or status queries.

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

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

It provides explicit, actionable instructions on how to define the operational area, offering two distinct geometric methods: defining a center point with a radius, or using an explicit bounding box (bbox). This leaves no ambiguity for the AI agent regarding input geometry.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.