get_weather

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

No annotations are provided, so the description bears the burden. It names the data source (Open-Meteo) and the metrics fetched, which adds context, but doesn't disclose anything about rate limits, failure behavior, accuracy caveats, or the hourly granularity implications beyond the word 'hourly'.

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?

Single, dense sentence; zero waste. Efficient phrasing that packs the data source and metric list into one line.

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 or annotations. For a moderately complex tool with 5 params and no param docs, a one-sentence description leaves the agent guessing at required coordinates, date format, and timezone meaning. The metric list helps, but it's thin for a data-fetching tool with no output schema.

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 coverage is 0% and all 5 parameters are undocumented in the description. The description mentions no parameters at all. Even the 'shoot window' phrasing implies date filtering, but latitude/longitude/timezone get zero explanation. The baseline low coverage means the description must compensate, and it doesn't.

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?

Clear verb+resource: 'Fetch hourly cloud cover, visibility, precipitation, wind and temperature' from Open-Meteo. The scope ('for a shoot window') positions it distinctly from siblings like get_astronomy and assess_dark_sky.

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 implies it's for weather during a shoot window, but doesn't explicitly state when to prefer it over siblings or when not to use it. It's distinguishable by content (clouds/visibility/precip/wind/temp) but no explicit alternatives or exclusions are given.

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