get_weather_forecast_content_israel

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

No annotations; description discloses it extracts and cleans (read operation) but doesn't detail what 'clean' entails or any side effects. Adequate but not rich.

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 sentence with no wasted words, front-loaded with purpose. Efficient.

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 no-param tool with output schema, description fully explains what it does and why, with no missing information.

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?

Zero parameters; schema coverage 100% trivially. Description adds value by explaining why the tool exists, meeting baseline for no params.

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?

Clearly states the tool extracts and cleans text content of the forecast page, with a specific purpose (so LLM can read it). Distinguishes from siblings like enter/select/open.

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?

Describes when to use (when forecast page is open and LLM needs to read it). No explicit when-not or alternatives, but context is clear.

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