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

With no annotations, the description carries the full burden. It discloses that the id must be a full URL discovered via the search tool, that the tool converts content to markdown or plain text, and that it retrieves 'full content'. It does not mention side effects, but for a fetch operation the read-only nature is implicit and sufficient given the output schema.

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: the first states the purpose and output, the second provides the prerequisite workflow. No filler words, front-loaded with the actionable verb.

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 a simple fetch with an output schema and fully documented parameters. The description covers the core operation and the critical workflow constraint, but does not elaborate on error handling or rate limits, which are less essential given the schema richness.

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 input schema already documents all three parameters with descriptions, reaching 100% coverage, so the description is not required to elaborate. It does reinforce the id requirement (full URL from search tool), but adds no new semantics beyond the schema.

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 specific verbs ('Fetch', 'convert') and identifies the resource ('MeteoSwiss webpage') and output formats (markdown/plain text). It clearly distinguishes this tool from the data-specific sibling tools (climate, weather, forecast, pollen, stations) and the search tool.

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 explicitly instructs to use the search tool first to discover valid page URLs before calling fetch, establishing a clear workflow. It does not explicitly state exclusions for using data tools, but the workflow guidance is strong enough for an agent to select this tool appropriately.

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