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

Annotations already declare read-only, idempotent, non-destructive behavior, lowering the burden. The description adds meaningful behavioral context by enumerating the exact fields returned (temperature, humidity, wind, pressure, etc.) and confirming global geocoding support. It does not mention units or data freshness, but those are minor given the annotation coverage.

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?

Three sentences with no waste: the first states what it does and what it returns, the second gives routing examples, and the third confirms input scope. Every sentence earns its place, and the key information is front-loaded.

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?

For a simple single-parameter tool with no output schema, the description is complete: it lists the output fields, provides routing examples, and defines acceptable input forms. An agent has everything needed to select and invoke it 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?

The schema fully describes the single parameter with examples ('Houston, TX', '77001', 'Paris'). The description repeats this same meaning with 'any city, zip code, or place name globally,' adding no new semantic detail beyond reinforcement, so the baseline of 3 applies.

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 uses a specific verb and resource ('Get current weather conditions') and clearly distinguishes itself by temporal scope—'current'—from sibling tools like weather_forecast. The examples further reinforce what the tool is for, making the purpose unambiguous.

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 description provides strong contextual guidance by listing several natural-language queries that should route here and stating it covers 'any current weather question.' It does not explicitly mention weather_forecast as the alternative for future conditions, so it lacks an exclusion, but the current-weather framing is clear.

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