Jina AI Remote 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 of behavioral disclosure and does so effectively. It describes the comprehensive analysis approach (examining HTTP headers, HTML metadata, Schema.org data, etc.), mentions the confidence scoring system, and specifies the return format (best guess timestamp and confidence level). It doesn't mention rate limits, authentication needs, or error conditions, but provides substantial behavioral context.

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 perfectly structured and concise - two sentences that efficiently convey the tool's purpose, methodology, and return values. Every element earns its place: the first sentence explains what the tool does and how it works, the second specifies the output format. No wasted words or redundant information.

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 single-parameter tool with no output schema, the description provides excellent context about the tool's behavior, methodology, and return format. It explains the comprehensive analysis approach and specifies what information will be returned (timestamp and confidence level). The only minor gap is the lack of explicit error handling or edge case information.

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% for the single 'url' parameter, so the schema already documents this parameter adequately. The description doesn't add significant meaning beyond what the schema provides - it mentions analyzing webpages but doesn't elaborate on URL format requirements, supported protocols, or edge cases beyond the schema's 'uri' format specification.

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 verb ('guess') and resource ('last updated or published datetime of a web page'), distinguishing it from sibling tools like 'read_url' or 'parallel_read_url' which focus on content extraction rather than timestamp inference. It explicitly defines the tool's unique function of analyzing multiple data sources to determine update times with confidence scoring.

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 about when to use this tool - when you need to determine when a webpage was last updated or published. However, it doesn't explicitly state when NOT to use it or mention alternatives among sibling tools, such as using 'read_url' for general content extraction instead of timestamp guessing.

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