analyze_url

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

No annotations are provided, so the description carries full burden. It states 'Powered by AI — no scraping needed,' implying external service usage but not detailing implications like rate limits, data handling, or URL accessibility. It does not disclose any destructive or side effects. The description covers basic behavioral traits but lacks depth for a tool that processes external URLs.

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?

The description is two paragraphs and a parameter line, front-loading the purpose and output. It is concise with no wasted words. Every sentence adds value. Slightly longer than strictly necessary due to the parameter documentation inline, but still 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?

Given the tool has only one parameter and an output schema exists, the description covers the core functionality and return values adequately. It lists specific output fields. However, it lacks mention of edge cases like invalid URLs, non-HTML pages, or performance considerations, but these are somewhat mitigated by the output schema's existence.

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 only parameter 'url' is described with a format hint ('e.g. "https://example.com/page"') and the requirement that it is a full URL. Though schema coverage is 0%, the description compensates by explaining the parameter beyond the schema's type string. The example adds practical guidance.

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 clearly states the tool analyzes a URL and returns a structured summary with specific output fields (title, summary, key points, topics, sentiment, reading time). It uses the specific verb 'analyze' and resource 'URL'. While it mentions 'no scraping needed' to differentiate, it does not explicitly compare to closely related siblings like 'read_url' or 'scrape_meta_tags', so a 4 is appropriate.

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 states when to use: 'Use this to understand what a web page is about without reading it.' This provides clear context. However, it does not mention when not to use or suggest alternatives, which would strengthen the guidance.

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