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jj-cheng25

weixin-articles-mcp

read_article

Read a WeChat Official Account article and return its title, body in Markdown, images (up to 10), and keyframes from up to 3 videos. Handles Tencent Video, WeChat-native, and Channels embeds.

Instructions

Read a WeChat Official Account article (mp.weixin.qq.com/s/...) and return its content as a multimodal block list:

  • First text block: title, account, publish time, cover URL, video count, and the full article body in Markdown.

  • Image blocks: the article's PNG/JPG images (GIFs filtered out, capped at 10) returned as native image content so the LLM can see them directly.

  • Per-video groups: a text marker video kind=... vid=... keyframes=N followed by N evenly-spaced keyframe images (capped at 3 videos).

On failure the response is a single text block starting with "Error:".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesA WeChat article URL, format: https://mp.weixin.qq.com/s/xxx
Behavior5/5

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

Despite no annotations, the description fully discloses behavior: return format (title, account, time, cover, video count, Markdown body), image handling (GIFs filtered, cap at 10), video keyframes (cap at 3), and error format (single text block starting with 'Error:'). This is comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed but efficiently structured: a concise overview followed by a well-organized list of return components. Every sentence adds value, though slightly verbose due to thoroughness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one parameter, no output schema, and no annotations, the description provides complete guidance: input format, full output structure with all edge cases (errors, caps, filtering). An agent can invoke it correctly without additional info.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage and a single parameter 'url' already described in schema, the description adds only marginal value by repeating the URL format and specifying it's for WeChat account articles. Baseline meets expectation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reads a WeChat Official Account article and returns its content as a multimodal block list. It specifies the URL format and details the output structure, leaving no ambiguity about the tool's function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly provide when or when not to use this tool, nor does it mention alternatives (though none exist in context). Usage is implied but not formally guided.

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

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