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zhihu-to-wechat
作者
dachenchen690-droid
· GitHub ↗
· v1.0.0
446
总下载
0
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1
当前安装
1
版本数
在 OpenClaw 中安装
/install zhihu-to-wechat
功能描述
全自动知乎热榜选题 → IT科技风格公众号文章生成 → 自动配图 → 微信服务号发布工作流。 当用户提到"知乎热点"、"公众号文章"、"帮我写公众号"、"热榜选题"、"微信推文"、"IT科技文章"、 "发布公众号"等场景时,必须触发此skill。适用于科技博主、IT自媒体、技术内容创作者。
安全使用建议
This skill appears to implement the advertised Zhihu→WeChat publishing workflow, but exercise caution before enabling it: 1) It requires sensitive credentials (WECHAT_APP_ID, WECHAT_APP_SECRET) and an image API key (Unsplash/Pexels). The registry metadata did not declare these — verify you are comfortable providing them. 2) The SKILL.md suggests saving secrets in the conversation context (not recommended). Prefer supplying credentials via environment variables or CLI args and avoid pasting AppSecret into chat history. 3) The publisher script caches the access token to ~/.wechat_token_cache.json — review and secure or delete that file if needed. 4) Because the skill executes bundled Python scripts that perform network downloads/uploads, review the scripts yourself or run them in an isolated environment (container/VM) before giving real credentials. 5) Confirm your WeChat service account has the required permissions and quotas, and be mindful of Unsplash/Pexels API rate limits. If you need higher assurance, ask the publisher to (a) update the manifest to list required env vars and primary credential, (b) remove the instruction to store secrets in conversation context, and (c) optionally provide a minimal audit or signed release of the code.
功能分析
Type: OpenClaw Skill
Name: zhihu-to-wechat
Version: 1.0.0
The 'zhihu-to-wechat' skill bundle is a legitimate automation workflow for content creators. It scrapes Zhihu hot topics, generates articles, fetches images from Unsplash/Pexels, and publishes drafts to WeChat. While it handles sensitive credentials (WECHAT_APP_ID/SECRET), they are used exclusively for official API interactions as described in 'wechat_publisher.py' and 'fetch_images.py'. The code is well-structured, lacks obfuscation, and the instructions in 'SKILL.md' are transparent and align with the stated purpose without any signs of malicious intent or prompt injection.
能力评估
Purpose & Capability
SKILL.md and the included scripts clearly require WeChat credentials (WECHAT_APP_ID, WECHAT_APP_SECRET) and an image API key (Unsplash/Pexels). However, the registry metadata declares no required env vars or primary credential. The actual capabilities (calling WeChat APIs, uploading images, saving tokens) are consistent with the described purpose, but the manifest omission of these sensitive dependencies is an incoherence that could mislead users about what secrets are needed.
Instruction Scope
Runtime instructions tell the agent to 'collect the following information and save it in the dialog context' (including AppSecret). Storing secrets in conversation context is risky because chat context may be logged or visible to other systems; the scripts themselves expect credentials via env vars or CLI args. The instructions otherwise stay within scope (web search for research, fetch Zhihu hot list, generate article, fetch images, format HTML, call WeChat APIs).
Install Mechanism
There is no install spec (instruction-only), which limits automatic disk modifications by an installer, but the skill bundles four executable Python scripts that the agent will run. Those scripts perform network I/O and write a token cache file to the user's home. No external download URLs or package installs are used, reducing supply-chain risk, but executing included code still has the normal runtime risk.
Credentials
The credentials requested by the workflow (WeChat AppID/AppSecret and Unsplash/Pexels keys) are proportionate to the described functionality. However, the skill metadata does not declare these env vars or a primary credential, which is misleading. The scripts also support reading credentials from environment variables and recommend exporting them — this should have been reflected in the manifest. The number and sensitivity of credentials is reasonable for the purpose, but the handling (saving to chat context, caching tokens to disk) raises privacy concerns.
Persistence & Privilege
The skill does not request 'always: true' and does not modify other skills. However, wechat_publisher writes a token cache file to the user's home (~/.wechat_token_cache.json) and will download/upload image binaries. That file-based caching is persistent and was not declared in the manifest; users should be aware tokens will be stored on disk.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install zhihu-to-wechat - 安装完成后,直接呼叫该 Skill 的名称或使用
/zhihu-to-wechat触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of zhihu-to-wechat skill.
- Automatically fetches top Zhihu trending topics and generates WeChat-style articles.
- Guides users through topic selection, content summarization, article creation, and WeChat draft publishing.
- Provides clear formatting standards and API usage instructions for WeChat Official Accounts.
- Includes key reminders for account requirements and token management.
元数据
常见问题
zhihu-to-wechat 是什么?
全自动知乎热榜选题 → IT科技风格公众号文章生成 → 自动配图 → 微信服务号发布工作流。 当用户提到"知乎热点"、"公众号文章"、"帮我写公众号"、"热榜选题"、"微信推文"、"IT科技文章"、 "发布公众号"等场景时,必须触发此skill。适用于科技博主、IT自媒体、技术内容创作者。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 446 次。
如何安装 zhihu-to-wechat?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install zhihu-to-wechat」即可一键安装,无需额外配置。
zhihu-to-wechat 是免费的吗?
是的,zhihu-to-wechat 完全免费(开源免费),可自由下载、安装和使用。
zhihu-to-wechat 支持哪些平台?
zhihu-to-wechat 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 zhihu-to-wechat?
由 dachenchen690-droid(@dachenchen690-droid)开发并维护,当前版本 v1.0.0。
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