Scrape Page

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

Annotations already flag that this is not read-only and is destructive, but the description adds crucial operational context: it consumes account credits, processes asynchronously, and requires inspecting the image library for results. This goes beyond the schema and annotations without contradicting them.

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?

Three short sentences, with the core purpose first, then cost, then async behavior. No filler or repetition of schema details.

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 tool with eight parameters and no output schema, the description gives the essential workflow: result location, async nature, and cost. It does not cover edge cases or detailed return structure, but the schema and annotations cover the rest.

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?

All eight parameters have schema descriptions, so the description carries little parameter burden. It adds no parameter-level details beyond the schema, but none are missing enough to lower the score.

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 concrete action and resource: 'Find images on a web page' and 'queue alt-text generation jobs'. This clearly separates it from direct-generation siblings such as generate_alt_text or generate_alt_text_from_file.

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?

It implies the intended use case (web page as source, asynchronous job queue) and notes results appear in the image library. However, it never explicitly names alternatives or states when not to use this tool, so routing guidance is left to inference.

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