wechat-article-writer

---

name: wechat-article-writer

description: End-to-end 微信公众号 (WeChat Official Account) article writing and publishing pipeline. 9-step multi-agent workflow: topic research → Chinese-first writing → blind quality review → fact-check → formatting → human preview → scrapbook illustrations → draft box publish. Use when user asks to write, draft, or publish a WeChat article, or says "forge write/draft/publish/topic/voice/status".

---

# wechat-article-writer

> 从选题到发布的公众号一体化写作工作流

Multi-agent pipeline: Orchestrator delegates writing and reviewing to independent subagents. The orchestrator never writes or reviews — it routes, tracks versions, and enforces quality gates.

Setup

bash <skill-dir>/scripts/setup.sh <workspace-dir>

Installs: bun runtime, bundled baoyu renderer deps, and a persistent preview server (`wechat-preview.service`, port 8898, auto-restart).

Scope

**Handles:** Topic research → Chinese-first writing → quality review → scrapbook illustrations → WeChat formatting → publishing to WeChat draft box (via Official Account API or CDP browser automation).

**Does NOT handle:** Git/version control, non-WeChat platforms, post-publish analytics, WeChat messaging/customer service.

**Ends at:** Article saved to WeChat draft box. User publishes manually.

---

Commands

Trigger any command below, or see `skill.yml` for the full trigger pattern list.

| Command | What it does |

|---------|-------------|

| `forge topic X` | Research trending angles, propose 3 options with hooks |

| `forge write X` | Full pipeline: research → publish (9 steps) |

| `forge draft X` | Write + format only, stop before illustrations/publish (steps 1-7) |

| `forge publish <slug>` | Publish an existing draft to WeChat |

| `forge preview <slug>` | Render preview, run format quality checks |

| `forge voice train` | Analyze past articles to extract voice profile |

| `forge status` | Show pipeline status and pending drafts |

If no subject given, loads from `session.json` (set by `forge topic`). See `references/data-layout.md`.

---

Pipeline (9 Steps)

State persists to `pipeline-state.json` — survives compaction. See `references/pipeline-state.md`.

| # | Step | Who | Details |

|---|------|-----|---------|

| 1 | **Research + Prep** | Orchestrator | (a) `web_search` for topic angles + 5-8 sources. (b) Verify each source exists (fetch title/authors/venue). Save as `sources.json`. (c) Load voice profile. (d) Generate outline (6-8 sections), save `outline.md`. |

| 2 | **Write** | Writer subagent | Chinese-first draft. Writer MUST cite only from `sources.json` or mark `[UNVERIFIED]`. See `references/writer-prompt.md` |

| 3 | **Review** | Reviewer subagent | Blind 8-dimension craft scoring. See `references/reviewer-rubric.md` |

| 4a | **Revise (auto)** | Writer subagent | Max 2 automated cycles. Loop back to Step 3 if score < threshold. |

| 4b | **Revise (human)** | Human-in-the-loop | If still below threshold after 2 auto cycles, user provides direction. Pauses pipeline. |

| 5 | **Fact-check** | Fact-Checker subagent | Verify every claim via web search. Produces corrections + reference list. Max 2 fact-check cycles (corrections → re-verify). See `references/fact-checker-prompt.md` |

| 6 | **Format** | Script | `bash scripts/format.sh <draft-dir> [draft-file] [theme]` — baoyu renderer (default theme: classic WeChat style). Themes: default/grace/simple. If fact-check required >3 text changes, Orchestrator does a **spot re-review** (Reviewer scores only changed paragraphs, not full article). |

| 7 | **Preview** | Human | Open `http://<host>:8898/formatted.html` (persistent preview server, systemd `wechat-preview.service`), await text approval |

| 8 | **Illustrate + Embed** | article-illustrator + script | Generate scrapbook images (AFTER text approval). ~$0.06/article via Z.AI (preferred, ~$0.015/image) or ~$0.50 via OpenRouter. |

| 9 | **Publish** | Orchestrator | **Three paths** — check in order: (C) WeChat Official Account API via appid+appsecret (credentials at `wechat_secrets_path` in config.json) — **preferred, most reliable**; (A) OpenClaw browser tool with base64 chunking for macOS/Titan; or (B) direct CDP WebSocket for Linux/remote. Paths A+B use two-phase injection (text first, then images via clipboard blob paste). See `references/browser-automation.md` |

Key Rules

Image Counts by Type

| Type | Min | Max |

|------|-----|-----|

| 科普 | 3 | 5 |

| 教程 | 3 | 6 |

| 观点 | 2 | 4 |

| 资讯 | 2 | 3 |

---

Review Dimensions

Reviewer scores 0-10 on **craft-observable** dimensions (not outcome predictions):

| Dimension | Weight |

|-----------|--------|

| Insight Density (洞察密度) | 20% |

| Originality (新鲜感) | 15% |

| Emotional Resonance (情感共鸣) | 15% |

| Completion Power (完读力) | 15% |

| Voice (语感) | 10% |

| Evidence (论据) | 10% |

| Content Timeliness (内容时效性) | 10% |

| Title (标题) | 5% |

**Pass:** weighted_total ≥ 9.0, no dimension below 7, Originality ≥ 8.

**Hard blockers (instant FAIL):** 教材腔, 翻译腔, 鸡汤腔, 灌水, 模板化, 标题党.

Full rubric with scoring criteria: `references/reviewer-rubric.md`

---

Architecture

Orchestrator (Main Agent) — routes, tracks, enforces gates
    ├── Writer Subagent — drafts + revises (Opus model)
    ├── Reviewer Subagent — blind scoring (Sonnet model)
    ├── Fact-Checker Subagent — verifies claims via web search (Sonnet model)
    └── article-illustrator — scrapbook images (after text passes)

---

Configuration

Configure via `~/.wechat-article-writer/config.json` (generated by `scripts/setup.sh`):

| Field | Default | Description |

|-------|---------|-------------|

| `default_article_type` | `"教程"` | Default article type (科普/教程/观点/资讯) |

| `wechat_secrets_path` | `~/.wechat-article-writer/secrets.json` | Path to WeChat API credentials |

| `chrome_debug_port` | `18800` | Chrome CDP port for browser automation (Path B) |

| `wechat_author` | — | Author name shown in WeChat draft |

| `word_count_targets` | See defaults | Min/max word counts per article type |

See `references/data-layout.md` for full config schema.

---

References

| File | When to load |

|------|-------------|

| `references/writer-prompt.md` | Step 2 (writing) and Step 4 (revision) |

| `references/reviewer-rubric.md` | Step 3 (review) — full 8-dimension scoring criteria |

| `references/fact-checker-prompt.md` | Step 5 — claim extraction, verification, correction protocol |

| `references/viral-article-traits.md` | Step 2 — Writer self-check list |

| `references/pipeline-state.md` | On resume or compaction — state machine schema + protocol |

| `references/browser-automation.md` | Step 9 — Two publishing paths: Path A (OpenClaw browser tool) and Path B (direct CDP). Includes base64 chunking, image insertion, save verification. |

| `references/LESSONS_LEARNED.md` | Hard-won lessons from production publishing sessions (escaping, selectors, mixed content, costs) |

| `references/data-layout.md` | Directory structure, slug generation, config/session schemas |

| `references/agent-config.md` | Setup — Gateway, AGENTS.md, environment config |

| `references/quality-checks.md` | Steps 3, 7 — content/format quality gates |

| `references/figure-generation-guide.md` | Step 8 — illustration placement heuristics |

| `references/wechat-html-rules.md` | Step 6 — what HTML/CSS works in WeChat |

| `references/templates.md` | Step 1 — starting templates by article type |

| `references/voice-profile-schema.json` | Step 1 — voice profile field definitions |

| `references/default-voice-profile.json` | Step 1 — fallback voice profile |