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WeChat Article Pipeline Example

Goal

Use Hermes Agent to write, detect AI-taste, de-AI-fy, and publish WeChat Official Account articles. The skill is continuously optimized using real account analytics data — not guesswork.

Maturity Level

L2 (semi-autonomous). Agent drafts the full article and generates diagrams. Human reviews and publishes. The analytics feedback loop runs weekly to refine title strategy, content structure, and topic selection.

Files

examples/wechat-article-pipeline/
├── SKILL.md              # wechat-viral-article skill (main pipeline)
├── scripts/
│   ├── ai_detect.py      # 8-dimension AI-taste scoring engine
│   └── de_ai.py          # AI-taste removal + repair instructions
└── references/
    └── article-template.md  # Obsidian YAML frontmatter template

How It Works

The 9-Step Writing SOP

Step 1: Topic selection   → 3 directions (source code / pitfalls / comparison)
Step 2: Research           → web search + official docs + GitHub issues
Step 3: Outline            → choose from 4 proven templates
Step 4: Draft              → 2000-4000 characters, inline image markers
Step 5: AI-taste detect    → scripts/ai_detect.py, target <20%
Step 6: De-AI-fy           → scripts/de_ai.py + 8-step manual method
Step 7: Generate diagrams  → draw.io CLI, brand color system
Step 8: Final check        → headline checklist + layout + image positions
Step 9: Save to Obsidian   → /今日头条/{title}.md with YAML frontmatter

The Analytics Feedback Loop

The skill includes real account data from July 2026 (13 followers, 8 articles, 238 recommendation reads/week) that validates:

  1. 「XXEngineering」naming convention is the strongest IP asset — Engineering-series articles averaged 81 reads vs 57 reads for non-series articles
  2. Concept/framework articles outperform tool/list articles — frameworks averaged 108 reads, tools averaged 55
  3. Recommendation algorithm favors high-completion + high-engagement content — publish every 2-3 days during the boost window

These findings are baked into the skill's hard requirements checklist: - Title format: XXEngineering: subtitle (mandatory) - Content type: concept/framework/methodology only (no tool lists) - Minimum 1 architecture diagram + 2 code screenshots - Ending: interactive question + next-preview teaser - AI concentration: <20%

Loop

  1. Read STATE.md to check the publishing schedule and next planned topic.
  2. Consult the performance data of past articles to select the next topic with highest potential.
  3. Agent writes the full draft following the 9-step SOP.
  4. Run scripts/ai_detect.py on the draft. If concentration >20%, run scripts/de_ai.py.
  5. Generate architecture diagrams via draw.io CLI (brand colors: #1a1a2e dark, #00d4ff blue).
  6. Save final article to Obsidian vault + paste into WeChat backend.
  7. Update STATE.md with publish date, actual reads after 48h, and lessons learned.

What Makes This Different

Most article-writing pipelines just generate text. This pipeline:

  • Detects and removes AI-taste programmatically (8-dimension rule engine + LLM-assisted rewrite)
  • Is data-driven — the skill file itself contains real analytics from the account's first month, so every writing decision is informed by what actually worked
  • Bakes the IP into the naming convention — the account's "XXEngineering" series identity is enforced at the title level
  • Generates professional diagrams via draw.io with a consistent brand color system

Dependencies

  • Hermes Agent v0.6+
  • draw.io desktop app
  • Obsidian vault at /Volumes/DISCa/Hermes Vault/Hermes Vault
  • Python 3.10+ (for ai_detect.py and de_ai.py)