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

With no annotations, the description carries the full burden and does substantial work: it declares that every value retains provenance, distance, age, measured/predicted status and confidence, that source divergence is surfaced, and that missing required evidence is named rather than estimated. That last clause is a meaningful behavioral promise an agent can rely on. It stops short of stating latency, cost, or any auth/permission requirements.

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 purpose is front-loaded, which is good, but the drone passage is redundant: 'separate model-derived precipitation and thunderstorm context is provided' is restated by 'the outcome includes wind and model precipitation and thunderstorm indications.' Trimming that duplication would tighten the definition noticeably.

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?

There is no output schema, so the description must convey the return shape, and it only does so at the level of properties (provenance, age, confidence, divergence) without any structure or example. For a five-parameter tool with fuzzy, provenance-rich output, an agent still cannot predict what it will receive or how divergence is represented.

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 100%, including ranges, the ISO 8601 format, the current-conditions-only restriction on time, and the field/domain aliasing rule, so the schema does the heavy lifting and baseline 3 applies. The description adds context about what the domain value changes for drones but does not explain lat/lng precision expectations, time semantics, or the effect of each domain value.

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 first sentence names a specific verb and resource: return physical-world evidence plus historical forecast reliability for a coordinate. That is materially more specific than the bare name, though the abstract phrasing 'physical-world evidence' forces the agent to infer concrete content. It does not name or contrast with siblings like get_forecast_trust or check_operability, which read as closely related.

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?

Usage is only implied: supply a coordinate, optionally a domain, with a drone-specific branch called out for precipitation/thunderstorm context. There is no explicit statement of when to prefer this over get_forecast_trust or check_operability, and no prerequisites. The 'not lightning detection' clause is a scope limit on the output rather than routing guidance.

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