Input
Two types of materials are needed:
- Insight summary: structured insights output by insight-extractor (
workspace/insights/*.md) - Raw content: transcripts, notes, reference materials (provide context and details)
Article generation process
Step 1: Determine the article positioning
Based on user instructions or automatic judgment:
| Dimension | Options |
|---|---|
| Platform | Blog / Zhihu / WeChat official account / Other |
| Style | Opinion piece / Tutorial / Retrospective / Dialogue style / Narrative |
| Length | Short (1-2K) / Medium (3-5K) / Long (5K+) |
| Audience | Tech community / General internet / Public |
| Tone | Laoguai style (casual + sharp) / Serious technical / Science-friendly |
Step 2: Select insights and materials
Choose from the insight summary:
- 1 main thesis: the article's core argument, must be clear and powerful
- 2-3 supporting points: argue the main thesis from different angles
- 1-2 golden lines: serve as the article's "memorable points"
- 1 controversy/twist: create reading tension
Supplement from the raw content:
- Specific cases, data, dialogue
- Scenes and details (increase authenticity)
Step 3: Build the article structure
Do not use AI boilerplate structures("First... second... finally...", "not X but Y").
Recommended structure patterns:
Pattern A: Story introduction → Insight explosion
- Start with a specific scene/story (taken from the materials)
- Lead into the core insight
- Expand the argument (use cases, not reasoning)
- Ending (leave an aftertaste, do not summarize)
Pattern B: Controversy entry → Two-sided development
- Throw out a controversial judgment
- Evidence for the affirmative side
- Evidence for the opposing side
- Your stance (clear and unambiguous)
Pattern C: Problem-driven → Layer-by-layer progression
- A specific problem
- The common but wrong answer
- The real answer (counterintuitive)
- Why everyone thought wrong
Step 4: Writing
Follow these rules:
Core writing principles
- Speak like a human: write for real people to read, not for search engines
- Have a stance: dare to say "this thing doesn't work," dare to say "I just like it"
- Give details: abstract opinions are worthless, concrete scenes have value
- Leave breathing room: short paragraphs, fast pace, not tiring to read
Anti-AI check (must check after writing)
Read the anti-AI rules for the corresponding platform:
- Technical article →
skills/zhiforge/references/anti-ai.md - Story/Novel →
skills/salt-story/references/anti-ai.md
General taboos:
- ❌ "Not… but…" sentence pattern
- ❌ Triple parenthetical explanations
xxx(即yyy) - ❌ Overuse of bold (more than 2 bold instances in a paragraph)
- ❌ "In conclusion," "To sum up," "It is worth noting that"
- ❌ Neat three-part/five-part structure
- ❌ Every paragraph is about the same length
How to cite source material
- Directly quote the speaker's original words (keep the colloquial feel): "He said something really harsh at the time—'xxx'"
- Don't turn colloquial speech into formal written language—formal written language actually feels fake
- Cite the source but don't make it academic: "This was mentioned in that livestream the other day"
Step 5: Self-check
After writing, check item by item:
- Is the title engaging? (Within 20 characters, with suspense or attitude)
- Can the first paragraph hook people? (3-second rule)
- Does it have an AI flavor? (Run through the anti-AI checklist)
- Are the punchy lines used?
- Does the ending summarize again? (Delete the summary paragraph)
Step 6: Output and archiving
Save to the corresponding directory:
- Blog → write directly into the blog repository's
_posts/ - Zhihu →
workspace/stories/zhihu/ - Other →
workspace/articles/
File format: Markdown, with YAML frontmatter (if it's a blog).
Publish
After the article is finished, choose the publishing method according to the target platform:
- Zhihu: call the
zhiforgeskill's publishing process (markdown import → fill in title → submit to question → publish) - Blog: git commit + push to GitHub Pages
- WeChat Official Account: export markdown, publish via the WeChat Official Account backend or API
Integration with other Skills
- Upstream:
insight-extractor(provides structured viewpoints),video-to-text(provides raw material) - Downstream:
zhiforge(Zhihu publishing),salt-story(if it needs to be adapted into a story) - Complete chain: video → transcript → viewpoints → article → publish