据 AlphaMoat 统计,截至 2026-09,Commerce Content Generator 累计下载 2,742 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 3,917 位,在「内容创作」分类(362 个)中排名第 258 位。

累计安装

248

累计下载

2,742

星标

全站排名

#3,917

全站前 78% · 「内容创作」前 72%

平台	累计安装	累计下载	星标	评论
ClawHub ↗	62	2,422	-	-
SkillHub ↗	248	2,742	1	—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

根据产品简介、证据、受众和渠道生成小红书、抖音、广告、邮件或商品页文案，并检查主张依据、标出证据缺口。发布前核验产品事实和平台要求，避免补写无证据的卖点。

资料发布于 2026-10-27

可以用来做什么

为商品生成多渠道文案草稿
检查宣传主张和证据支持

什么时候用

需要将产品资料改写成营销内容时
核对文案中的产品卖点时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

根据产品资料生成商品页和社交文案，并列出每项主张的证据。

标记缺失证明的卖点，不要发布草稿。

月度数据趋势

累计下载2,742

星标1

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份	累计下载	环比	星标
2026-09	2,742	—	1
2026-08	2,307	+6.0%	1
2026-07	2,177	+11.7%	1
2026-06	1,949	+18.5%	1
2026-05	1,645	—	-
2026-03	1,105	—	-

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 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

展开全部(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.