Websearch MCP Server

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds valuable context beyond annotations by specifying the conversion method ('html-to-markdown'), performance aspect ('high-performance'), and token usage reduction, which helps the agent understand practical implications. No contradiction with annotations.

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 sentences, front-loaded with the core purpose and followed by implementation details and benefits. Every sentence adds value: the first defines the tool's function, and the second explains the conversion method and efficiency gains, with no wasted words.

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's moderate complexity, rich annotations (covering safety and behavior), and the presence of an output schema (which handles return values), the description is complete enough. It covers the purpose, method, and key benefits, leaving structured fields to detail parameters and outputs, making it well-rounded for agent use.

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 description coverage is 100%, so the schema fully documents all parameters. The description does not add any parameter-specific details beyond what the schema provides, such as explaining URL validation or metadata content. It only mentions the overall output format ('clean markdown'), which aligns with the baseline for high schema coverage.

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 specific action ('fetch a URL'), resource ('its content'), and transformation ('as clean markdown'), distinguishing it from siblings like websearch_search (which likely returns search results) and websearch_search_and_fetch (which combines search and fetch). It explicitly mentions the conversion method ('html-to-markdown') and benefit ('dramatically reduces token usage').

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 implies usage by stating it fetches a URL and converts to markdown, but it does not explicitly say when to use this tool versus alternatives like websearch_search_and_fetch. It mentions the benefit of reduced token usage, which provides some context, but lacks clear guidance on prerequisites or exclusions.

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