Perplexity MCP Server

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

With no annotations provided, the description carries the full burden and does so effectively. It discloses key behavioral traits: uses browser automation and Readability library, handles JavaScript rendering, includes fallback logic, special handling for GitHub URLs, performs pre-checks for content types and HTTP status, and notes limitations with complex pages. This covers technical implementation, error handling, and edge cases.

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 appropriately sized and front-loaded with the core purpose in the first sentence. Each subsequent sentence adds valuable information (technologies, special cases, checks, ideal use, limitations). There is minimal waste, though it could be slightly more streamlined.

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 complexity (dynamic content extraction, fallback logic, GitHub handling) and the presence of an output schema (which means return values are documented elsewhere), the description is complete enough. It covers purpose, technology, behavior, use cases, and limitations without needing to repeat structured data.

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 already documents both parameters (url and depth) thoroughly. The description does not add any additional meaning about parameters beyond what the schema provides, such as explaining how depth affects recursive exploration in practice. Baseline 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'extract the main article text content from a given URL' using specific technologies (Puppeteer and Mozilla's Readability). It distinguishes from siblings by focusing on content extraction rather than chat, code analysis, API discovery, documentation retrieval, or general search.

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 context for when to use it ('Ideal for getting clean text from articles/blog posts') and includes a note about limitations ('May struggle... on complex homepages or dashboards'). However, it does not explicitly mention when NOT to use it or name specific alternatives among sibling tools.

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