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

With no annotations, the description bears the full burden of behavioral disclosure. It does reveal an external dependency ("via Open-Meteo") and implies a read-style operation, but it says nothing about response units/format, error behavior, rate limits, or the fact that 8 of the 9 schema parameters are unrelated to weather lookup and are discarded.

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?

A single eight-word sentence with zero filler; every word ("Current", "temperature", "city", "Open-Meteo") earns its place and the key signal is front-loaded. It is efficient, though borderline terse enough to read as a noun phrase rather than an actionable instruction.

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?

The tool is more complex than the description acknowledges: 9 optional parameters, no required params, no annotations, and no output schema. The one-line description does not specify which parameter to pass, what the hint looks like, or why the other parameters exist, so an agent cannot invoke it confidently.

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 the baseline is 3. The description reinforces that `city` is the operative parameter, but it adds no meaning beyond the schema and does nothing to resolve the ambiguity of the other eight unrelated optional parameters (ref, url, feed, json, path, zone, query), leaving an agent guessing about which are valid inputs.

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 names a specific resource and data source: current temperature, a city, and Open-Meteo. It is clear about what the tool returns, though it lacks an explicit verb and does not explicitly differentiate itself from siblings like geo-hint or lib-docs-hint.

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 implied: use this when you need the current temperature for a city. There is no explicit when/when-not guidance, no named alternatives, and no prerequisites, so an agent must infer the selection criteria from the weather domain alone.

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