wechat-article-aggregator

Name: wechat-article-aggregator
Author: wwwzhouhui

Writing Verified v1.0.0

Repo stars 244
Author updated Live
Author repo skills_collection

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: Writing
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 92 / 100 · audit passed
Author / version / license: @wwwzhouhui · v1.0.0 · no license declared
Token usage: Lean
Setup complexity: Plug-and-play
External API key: Not required
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: Python
Permissions: Read-only
Write / modify
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview wechat-article-aggregator.preview

---
name: wechat-article-aggregator
description: 通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。 获取单个公众号最新 2 篇文章： python scripts…
category: writing
runtime: Python
---

# wechat-article-aggregator output preview

## PART A: Task fit
- Use case: 通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。 获取单个公众号最新 2 篇文章： python scripts/fetcharticles.py --api-key YOURKEY --fakeids "MzkzNDQxOTU2MQ==" 获取多个公众号文章（逗号分隔 fakeid）： runs entirely locally; runs on Python. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “快速开始 / 依赖安装 / 用户参数说明” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。 获取单个公众号最新 2 篇文章： python scripts/fetcharticles.py --api-key YOURKEY --fakeids "MzkzNDQxOTU2MQ==" 获取多个公众号文章（逗号分隔 fakeid）： runs entirely locally; runs on Python. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “快速开始 / 依赖安装 / 用户参数说明” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: wechat-article-aggregator
description: 通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。 获取单个公众号最新 2 篇文章： python scripts…
category: writing
source: wwwzhouhui/skills_collection
---

# wechat-article-aggregator

## When to use
- 通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。 获取单个公众号最新 2 篇文章： python scripts/fetcharticles.py --ap…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “快速开始 / 依赖安装 / 用户参数说明” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "wechat-article-aggregator" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> 快速开始 / 依赖安装 / 用户参数说明
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> Python | read files, write/modify files | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: 通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。获取单个公众号最新 2 篇文章： python scripts/fetcharticles.py --api-key YOUR…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “快速开始”, “依赖安装”, “用户参数说明”, “API Key 获取方式”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name wechat-article-aggregator directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “快速开始 / 依赖安装 / 用户参数说明” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

微信公众号文章聚合器

通过 mptext.top API 批量获取指定公众号博主的最新文章，下载并解析为 Markdown/HTML/纯文本格式输出。

快速开始

获取单个公众号最新 2 篇文章：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids "MzkzNDQxOTU2MQ=="

获取多个公众号文章（逗号分隔 fakeid）：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids "MzkzNDQxOTU2MQ==,MjM5NDI4MTY3NA==" --limit 3

按公众号名称获取：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids "赛博禅心,饼干哥哥AGI"

获取所有预置公众号的文章：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids all --limit 2

依赖安装

pip install requests beautifulsoup4 html2text

最低依赖: 仅 requests 为必须依赖。beautifulsoup4 和 html2text 用于增强 Markdown 转换效果，未安装时会使用内置 HTML 解析器。

用户参数说明

参数	类型	必填	默认值	说明
`--api-key` / `-k`	string	是	-	mptext.top 的 API Key
`--fakeids` / `-f`	string	是	-	公众号 fakeid 列表（逗号分隔）、公众号名称、或 `all`
`--limit` / `-l`	int	否	2	每个公众号获取的文章数量
`--output-dir` / `-o`	string	否	`./output`	输出目录
`--format` / `-F`	string	否	`markdown`	输出格式：`markdown` / `html` / `text` / `json`
`--accounts-file` / `-a`	string	否	自动查找	自定义公众号账号列表 JSON 文件路径
`--interval` / `-i`	float	否	1.0	请求间隔秒数
`--list-accounts`	flag	否	-	列出所有预置公众号信息

API Key 获取方式

API Key 来源于 mptext.top 平台，用于认证文章获取请求。在请求头中以 X-Auth-Key 传递。

fakeid 说明

fakeid 是微信公众号的唯一标识（Base64 编码的 biz 参数），可通过以下方式获取：

在微信公众号平台后台查看
从公众号文章 URL 中的 __biz 参数提取
使用本 skill 预置的账号列表

功能说明

1. 获取文章列表

调用 mptext.top API 获取指定公众号的最新文章列表：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids "MzkzNDQxOTU2MQ==" --limit 5

2. 下载并解析文章内容

获取文章 HTML 后自动提取 #js_content 正文区域，转换为 Markdown 格式：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids "赛博禅心" --format markdown

3. 批量获取多个公众号

同时获取多个公众号的最新文章：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids "赛博禅心,饼干哥哥AGI,老金开源" --limit 3

4. 获取所有预置公众号

使用 all 关键字获取所有预置公众号的文章：

python scripts/fetch_articles.py --api-key YOUR_KEY --fakeids all

5. 查看预置公众号列表

python scripts/fetch_articles.py --api-key dummy --fakeids dummy --list-accounts

6. 作为 Python 库调用

import sys
sys.path.insert(0, 'scripts')
from fetch_articles import get_article_list, download_article_html, extract_markdown_from_html, load_accounts, resolve_fakeids, fetch_all

api_key = "YOUR_API_KEY"

# 获取单个公众号文章列表
articles = get_article_list(api_key, "MzkzNDQxOTU2MQ==", limit=2)
for art in articles:
    print(art['title'], art['url'])

# 下载并解析文章内容
html = download_article_html(api_key, articles[0]['url'])
markdown = extract_markdown_from_html(html, title=articles[0]['title'])
print(markdown[:500])

# 批量获取多个公众号
accounts = load_accounts()
fakeids = resolve_fakeids("赛博禅心,饼干哥哥AGI", accounts)
summary = fetch_all(api_key, fakeids, limit=2, output_dir="./output")
print(f"成功: {summary['success']}, 失败: {summary['fail']}")

输出结构

output/
├── 赛博禅心/
│   ├── 文章标题1.md
│   └── 文章标题2.md
├── 饼干哥哥AGI/
│   ├── 文章标题1.md
│   └── 文章标题2.md
├── 老金开源/
│   └── ...
└── summary.json          # 所有文章的元数据汇总

summary.json 格式

{
  "fetch_time": "2026-02-23T17:30:00",
  "total_accounts": 3,
  "total_articles": 6,
  "success": 5,
  "fail": 1,
  "accounts": [
    {
      "fakeid": "MzkzNDQxOTU2MQ==",
      "name": "赛博禅心",
      "articles": [
        {
          "title": "文章标题",
          "url": "https://mp.weixin.qq.com/s/...",
          "create_time": "1708689600",
          "saved_path": "output/赛博禅心/文章标题.md",
          "status": "success"
        }
      ]
    }
  ]
}

API 接口说明

文章列表接口

GET https://down.mptext.top/api/public/v1/article?fakeid={URL_ENCODED_FAKEID}&limit={N}

参数	说明
`fakeid`	公众号的 fakeid，需 URL 编码（`==` → `%3D%3D`）
`limit`	返回文章数量

请求头：

X-Auth-Key: {YOUR_API_KEY}

响应示例：

[
  {
    "title": "文章标题",
    "url": "https://mp.weixin.qq.com/s/xxxxx",
    "create_time": 1708689600
  }
]

文章下载接口

GET https://down.mptext.top/api/public/v1/download?url={URL_ENCODED_ARTICLE_URL}&type=html

参数	说明
`url`	微信文章 URL，需 URL 编码
`type`	固定为 `html`（API 返回 HTML 格式）

请求头：

X-Auth-Key: {YOUR_API_KEY}

响应： 完整的微信文章 HTML 页面。

HTML 正文解析规则

从下载的 HTML 中提取正文内容：

定位 id="js_content" 的 div 元素
移除 script、style、noscript 标签内容
提取文本内容，保留段落换行
使用 html2text 转换为 Markdown（如已安装）

预置公众号列表

序号	公众号名称	分类	FakeID
1	饼干哥哥AGI	AI编程	`MjM5NDI4MTY3NA==`
2	赛博禅心	AI前沿	`MzkzNDQxOTU2MQ==`
3	可怜的小互	AI技术	`MzkzMTcyMTgxNg==`
4	宝玉的工程技术分享	技术翻译	`Mzk1NzgxMjQ0OA==`
5	苍何	AI实战	`Mzg3MTk3NzYzNw==`
6	老金开源	Claude Code	`MzI0NzU2MDgyNA==`
7	玩转AI工具	AI工具	`MzU4NTE1Mjg4MA==`
8	袋鼠帝AI客栈	AI实战	`MzkwMzE4NjU5NA==`

可通过 --accounts-file 参数指定自定义的公众号列表 JSON 文件来扩展。

注意事项

API Key 安全: 请勿将 API Key 硬编码到代码中，建议通过环境变量或命令行参数传入。
请求频率: 默认间隔 1 秒，如遇 429 错误请增大 --interval 值。
HTML 解析: 下载接口返回完整 HTML 页面，脚本自动从 #js_content 区域提取正文。
依赖降级: 未安装 beautifulsoup4 和 html2text 时，使用内置 HTMLParser 提取纯文本。
文件命名: 输出文件以文章标题命名，自动去除特殊字符，长度截断为 80 字符。

触发关键词

"获取公众号文章"
"抓取微信文章"
"公众号文章聚合"
"批量获取公众号"
"下载公众号文章"
"微信文章采集"
"获取最新公众号文章"

更新日志

v1.0.0 (2026-02-23)

初始版本
支持通过 mptext.top API 获取公众号文章列表
支持下载文章 HTML 并解析为 Markdown/HTML/Text/JSON
内置 HTMLParser 提取 #js_content 正文（零依赖降级方案）
预置 8 个热门 AI 技术公众号 fakeid
支持按公众号名称或 fakeid 获取
支持 all 关键字获取所有预置公众号
自动生成 summary.json 汇总元数据

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add wwwzhouhui/skills_collection/wechat-article-aggregator -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

92 / 100

Verified

未声明 license/许可。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
wwwzhouhui/skills_collection
Version: 1.0.0
中文

More by @wwwzhouhui

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Category & tags

Category Writing