WeChat Article Summary
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Please follow https://skillhub.cn/install/skillhub.md and install @user_909957f0/summary-is-all-you-need.
About this skill
Problem to solve
WeChat articles often mix navigation, ads, comments, and unrelated recommendations. Pasting that raw text into a model can produce summaries that simply repeat the title and add generic remarks. This skill separates extraction from summarization: a unified reader produces structured content, and the final summary is based on content_text, not only the title or description. It is aimed at longer pieces where the useful question is what conclusion the material wants the reader to accept, what evidence supports it, and what should be remembered or done.
How it works
- Unified reading: supports
wechat,generic-web,pdf,docx,markdown,text, andraw-textsources. For WeChat posts it uses a bundledmp.weixin.qq.comextractor to preserve article text while ignoring ads, sidebars, and comments where possible. - Reading-purpose identification: before writing, it classifies the material as fact retrieval, concept understanding, method learning, opportunity judgment, object evaluation, viewpoint formation, or mixed, then asks what question it answers, what conclusion it pushes, and what evidence, examples, or reasoning support that conclusion.
- Material-type focus: news summaries prioritize confirmed facts, timeline, uncertainty, and open follow-up; opinion pieces focus on claim, assumptions, counterarguments, and bias; technical reports focus on research question, evidence chain, findings, limitations, and decision implications.
- Output constraints: the response follows a fixed section order and avoids vague phrases such as “important significance” or “worth attention.” Uncertain points are marked as
not stated in the source, and key professional concepts are usually limited to 2–4 explanations with plain analogies.
Boundaries
It is better at interpreting and distilling than mechanically extracting. If the page is anti-scraping, the PDF is scanned, the article is too short, or extraction fails, it asks for copied text, saved HTML/PDF, Word/Markdown files, or other alternative material. The summary remains Chinese-oriented, avoids inventing facts, and for marketing posts, resumes, or papers it tends to expose intent, evidence gaps, and actionable conclusions rather than restating each section.
Use Cases
- Extract the main text of a long WeChat article before passing it to a model, then identify the conclusion the author wants readers to accept.
- Compare PDF reports, web articles, and WeChat explainers to produce facts, evidence, and uncertainty items.
- Review marketing copy to identify its value proposition, target user, proof gaps, and possible exaggerated claims.
- Compress technical papers or reports into research questions, evidence chains, limitations, and decision implications.
Best For
- Content analysts who need to turn multiple long industry WeChat posts into citable summaries
- Researchers who need to check consistency across papers, reports, and web explainers
- Growth analysts who need to assess marketing claims and evidence gaps
- Independent researchers who want to normalize WeChat, PDF, and Word material into knowledge notes
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