read_article

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

With no annotations provided, the description takes on full disclosure burden. It reveals that the tool uses Jina AI Reader, includes a free service rate limit of 100 RPM, enforces a 5-second interval between requests, and may fail on paywalled or login-protected pages. It also states that ads and navigation noise are removed. This is substantial behavioral context, though it does not cover error handling or authentication details.

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 well-structured with a clear opening summary, a typical flow section, parameter explanations, a return-value note, examples, and usage notes. It is concise yet comprehensive, with every sentence adding value. The front-loaded summary makes the purpose immediately clear.

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 2 parameters, no annotations, and an output schema not shown, the description is complete. It covers the input parameters, return format (JSON with Markdown), rate limits, usage flow, examples, and potential failure cases. The presence of an output schema makes the return-value explanation sufficient, and the description fills all other gaps.

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 0%, so the description fully compensates by explaining both parameters: url is required and must start with http:// or https://, and timeout is the request timeout in seconds (default 30, max 60). It also marks url as required (必需). This goes beyond the raw schema and gives complete semantic guidance.

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 that the tool reads article content from a specified URL and returns LLM-friendly Markdown. It explicitly names the resource (article content) and the action (read), and differentiates itself from sibling tools such as search_news and read_articles_batch by focusing on single-URL reading for analysis.

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 an explicit typical usage flow: first use search_news to get links, then use read_article to fetch content. It also lists appropriate use cases (reading news, getting article details, analyzing content) and notes limitations (paywall pages may fail). However, it does not explicitly contrast with read_articles_batch for batch scenarios, so it falls short of a full when-not-to-use guidance.

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