read_article

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

No annotations are provided, so the description carries the full burden. It discloses that the tool uses Jina AI Reader, transforms pages to clean Markdown, and has rate limits (100 RPM) with a 5-second built-in delay. It also notes limitations with paywalled/content-gated pages. This is good transparency, though it does not mention error handling or authentication requirements, which is a minor gap.

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 comprehensive but well-structured with clear sections (purpose, usage flow, args, returns, examples, notes). It front-loads the core purpose, then provides actionable guidance. While lengthy, every section adds value (usage flow, parameter details, rate limits, example), so it is appropriate for the tool's complexity without being bloated.

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 (2 parameters, no annotations, external service dependency), the description covers essential operational context: the Jina AI dependency, rate limits, usage workflow, and an example. An output schema exists, so return format details are not needed. Missing only explicit disambiguation from the batch sibling, but otherwise complete for an agent to call it correctly.

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 must compensate. It fully describes both parameters: url requires http:// or https:// and is mandatory; timeout is in seconds with default 30 and maximum 60. This goes beyond the schema by explaining URL format and timeout constraints, making parameter usage unambiguous.

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 reads article content from a specified URL and returns LLM-friendly Markdown. It specifies the verb (read), resource (article content), and output format. It distinguishes itself from sibling tools by emphasizing single-URL operation and providing a typical workflow that pairs with search_news, but it does not explicitly mention the batch variant (read_articles_batch) or contrast with it, so differentiation is slightly implicit.

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 a clear 'typical usage flow' (search → read → analyze), and states suitable use cases ('reading news, getting article details, analyzing content'). It gives practical context on when to use the tool, including the dependency on search_news for obtaining URLs. However, it does not explicitly state when not to use it or mention alternative tools like read_articles_batch for multiple URLs, so exclusions are missing.

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