fetch_article

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

With no annotations, the description carries full burden and discloses key behaviors: parsing to Markdown and conditional caching. It mentions that setting save=True writes back if the article exists. It could further clarify behavior for save=False or when the article is not found, but the provided details are sufficient.

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 extremely concise with two sentences and a code block. Every sentence adds value, and the structure is front-loaded with the main action, followed by parameter details.

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 only two parameters and no output schema or annotations, the description covers the essentials: the task, URL constraint, and caching behavior. It lacks details on error handling or output format, but given the simplicity, it is nearly complete.

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?

The schema has 0% description coverage, so the description adds essential meaning: it explains that 'url' must be a specific type of WeChat link and that 'save' controls caching behavior. This goes beyond the schema's type definitions.

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 action: fetching an article's full body, parsing to Markdown, and optionally caching. It specifies the required URL format (mp.weixin.qq.com/s/...), distinguishing it from sibling tools like crawl_incremental or list_articles_page.

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 the tool (to fetch a single article) and includes a specific URL constraint. However, it does not explicitly state when not to use it or mention alternatives, though the sibling tools offer natural differentiation.

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