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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds useful behavioral detail beyond that: rotating proxies, JavaScript rendering, and configurable output format. It does not contradict any annotation.

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 three well-structured sentences plus a clear example, with the core purpose front-loaded. Every sentence adds a distinct piece of information—purpose, output options, key flags—and nothing is redundant.

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 7-parameter tool with no output schema, the description covers general usage, output formats, and the most important tuning flags. It omits autoparse, but the schema fully describes that parameter, and the example gives a realistic invocation. Overall sufficient for correct invocation.

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 100%, so the schema already documents all parameters. The description adds extra meaning by explaining markdown is 'ideal for feeding an LLM' and providing a combined usage example. This is above the baseline for fully covered schemas.

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 scrapes any web page through ScraperAPI and returns content, with a specific verb and resource. It implicitly differentiates from specialized siblings by using 'any web page', but does not explicitly name alternatives like scraperapi_amazon_product.

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 gives concrete usage context for render, premium, country_code, and output_format, recommending markdown for LLM consumption. However, it lacks explicit 'when not to use' guidance or mention of specialized sister tools, so it falls short of a 5.

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