← Back to Skills Marketplace
zhihu-to-wechat
by
dachenchen690-droid
· GitHub ↗
· v1.0.0
446
Downloads
0
Stars
1
Active Installs
1
Versions
Install in OpenClaw
/install zhihu-to-wechat
Description
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。
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install zhihu-to-wechat - After installation, invoke the skill by name or use
/zhihu-to-wechat - Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Frequently Asked Questions
What is zhihu-to-wechat?
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。 It is an AI Agent Skill for Claude Code / OpenClaw, with 446 downloads so far.
How do I install zhihu-to-wechat?
Run "/install zhihu-to-wechat" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is zhihu-to-wechat free?
Yes, zhihu-to-wechat is completely free (open-source). You can download, install and use it at no cost.
Which platforms does zhihu-to-wechat support?
zhihu-to-wechat is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created zhihu-to-wechat?
It is built and maintained by dachenchen690-droid (@dachenchen690-droid); the current version is v1.0.0.
More Skills