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

Annotations already declare this as a safe, idempotent, closed-world read, and the description usefully adds behavioral scope: it reports fit status and conditional (not calibrated) uncertainty, and explicitly excludes object identification. These expectations about output meaning are meaningful added context beyond the structured hints.

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?

Two dense sentences that front-load the operation, the model, and the range constraint, then close with output expectations and explicit limitations. No filler.

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?

Given an output schema exists, the description need not explain return values, and it still summarizes the output (fit status, conditional uncertainty). For a complex nested-input compute tool the key semantic concepts and limitations are covered, leaving only field-level detail unaddressed.

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?

Schema description coverage is effectively 0% for the single deeply nested 'observers' parameter, so the description must compensate. It partially does by mapping observers to 'tracks', sigma to 'angular noise', and clock_offset to 'clocks', but never explains lat/lon/elevation_m/samples/t_s semantics.

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?

States a precise verb and resource ('Fit position/velocity from 2–4 supplied azimuth/elevation tracks') plus the underlying model (constant velocity in spherical ECEF). This is highly specific and lets an agent tell what it does without opening the schema, though it never names or contrasts a sibling tool.

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?

The input constraints (2–4 tracks) imply when the tool is applicable, but there is no explicit when-to-use guidance or routing to alternatives such as compute_orbit or analyze_kinematics. Usage is left to inference.

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