據 AlphaMoat 統計,截至 2026-09,Commerce Content Generator 累計下載 2,742 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,917 位,在「內容創作」分類(362 個)中排名第 258 位。

累計安裝

248

累計下載

2742

星標

全站排名

#3,917

全站前 78% · 「內容創作」前 72%

平台	累計安裝	累計下載	星標	評論
ClawHub ↗	62	2422	-	-
SkillHub ↗	248	2742	1	—

各平台的計數口徑不同,統計時間不一致。

這個技能是做什麼的

根據產品簡介、證據、受眾和渠道生成小紅書、抖音、廣告、郵件或商品頁文案，並檢查主張依據、標出證據缺口。釋出前核驗產品事實和平台要求，避免補寫無證據的賣點。

資料釋出於 2026-10-27

可以用來做什麼

為商品生成多渠道文案草稿
檢查宣傳主張和證據支援

什麼時候用

需要將產品資料改寫成行銷內容時
核對文案中的產品賣點時

示例提示詞

以下是根據技能文件生成的示例,不代表實際執行結果。

根據產品資料生成商品頁和社交文案，並列出每項主張的證據。

標記缺失證明的賣點，不要釋出草稿。

月度資料趨勢

累計下載2742

星標1

2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。

月份	累計下載	環比	星標
2026-09	2742	—	1
2026-08	2307	+6.0%	1
2026-07	2177	+11.7%	1
2026-06	1949	+18.5%	1
2026-05	1645	—	-
2026-03	1105	—	-

SKILL.md 原文

以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。

2.8 KB · ClawHub v1.2.0

---
name: content-generator
description: "Commerce content generator. Input a product brief, evidence, audience, and channel; output Xiaohongshu notes, Douyin scripts, ad/email/listing variants, and a claims checklist. Evidence-aware: does not invent unsupported claims and flags missing proof."
---
# Content Generator

Create platform-ready commerce content without inventing unsupported claims.

## Workflow

展開全部(共 66 行)

1. Capture the product brief:
   - product name, category, price or price range
   - target audience and use scenario
   - benefits, differentiators, proof points, limitations
   - platform, tone, length, conversion goal
   - forbidden claims or regulated categories
2. If the brief is thin, ask for the missing business-critical facts. If the user wants speed, continue with explicit assumptions and mark `待补充证据`.
3. Select the right output pack:
   - Xiaohongshu: personal discovery note, practical list, comparison note
   - Douyin: short-video hook, spoken script, captions, CTA
   - Live selling: opening, demo flow, objections, close
   - Moments: concise social recommendation
   - Zhihu: rational evaluation and purchase advice
   - Marketplace: title, bullets, detail-page sections
   - Ads: A/B angle variants and CTA options
4. Draft using only user-provided facts or clearly labeled assumptions.
5. Run a quality pass before final output: evidence, platform fit, claim safety, specificity, and next data needed.

## Deterministic Pack Generator

When the user wants a structured first draft, batch variants, or repeatable output, use:

```bash
node scripts/generate_content_pack.js --input product.json --format markdown
```

The input JSON can include:

```json
{
  "name": "HydraGlow Cream",
  "category": "美妆",
  "price": "299",
  "audience": "commuters with dry skin",
  "scenario": "winter office skincare",
  "benefits": ["light texture", "long-lasting moisture"],
  "evidence": ["user test: 8-hour office day"],
  "limitations": ["not a medical treatment"],
  "tone": "calm and trustworthy",
  "platforms": ["xiaohongshu", "douyin", "marketplace"]
}
```

Read `references/platform-playbook.md` when platform details matter. Read `references/quality-checklist.md` before publishing, reviewing risky copy, or handling health, finance, legal, children, food, supplements, or high-priced products.

## Output Contract

For user-facing answers, prefer this shape:

- `Brief`: product, audience, goal, assumptions.
- `Content`: platform-specific drafts.
- `Quality Notes`: unsupported claims, risky phrases, missing evidence.
- `Next Iteration`: what data would improve conversion or trust.

Do not claim guaranteed outcomes, medical effects, investment returns, legal compliance, official endorsement, scarcity, or comparative superiority unless the user supplied reliable evidence.