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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: reels are returned newest-first and include watch links. This goes beyond the annotations without contradicting them.

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 sentences, no filler. The first sentence front-loads the purpose and value proposition; the second gives use cases and output ordering. Every word earns its place.

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?

With an output schema present, the description does not need to detail return fields. It covers what the tool does, when to use it, and what to expect (newest-first, watch links). The tool has only optional params, so the agent has enough to decide and call correctly.

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%, so all four parameters already have clear descriptions in the schema. The description adds no additional parameter semantics beyond the schema, such as format details or relationships. It meets the baseline for high coverage but does not elevate it.

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 description states a specific resource (archived storm timelapses with burned-in accumulation data), names the tool's purpose ('Proof of Powder'), and provides concrete example queries that differentiate it from siblings like get_storm_watch or get_snow_history. The verb is implicit but the noun and scope are crystal clear.

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 explicitly gives example queries ('how much did it snow at X last night', 'show me the storm at Alta') and states 'Use for ... or any request for storm footage / timelapse / receipts.' It does not name alternatives or exclusions, but the examples are strong enough to guide an agent on when to call it.

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