extract_content

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering safety. The description adds behavioral specifics (removes ads, nav, footers, boilerplate) without contradicting annotations, enhancing transparency.

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 focused sentences including an example, with no wasted words. It is front-loaded with the main action. Could be slightly more concise but adequately sized.

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?

No output schema exists, and the description does not describe the return format. It adequately covers purpose and usage but lacks details on output structure or error behavior. For a simple tool, it is moderately complete.

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 covers 100% of parameters with descriptions (url and options). The description includes an example URL but does not elaborate on the options parameter beyond what the schema provides. Given high schema coverage, the description adds minimal parameter meaning.

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 explicitly states it extracts a clean, readable version of web articles by removing ads, nav, etc., and distinguishes itself from extract_text by preferring it for article-style pages. This provides a specific verb+resource and differentiates from siblings.

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 provides clear use cases (RAG ingestion, summarization, LLM context) and explicitly advises preferring this over extract_text for article-style pages, giving a comparison. It lacks explicit when-not-to-use scenarios but offers sufficient guidance.

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