Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add redfox-data/redfox-community-dsh --skill xiaohongshu-note-analyzergit clone --depth 1 https://github.com/redfox-data/redfox-community-dshWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/redfox-data/redfox-community-dsh/xiaohongshu-note-analyzer)<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/xiaohongshu-note-analyzer"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/xiaohongshu-note-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/xiaohongshu-note-analyzer"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/xiaohongshu-note-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00054 | $0.03297 |
| Opus 5 | $0.00027 | $0.01648 |
| Sonnet 5 | $0.00011 | $0.00659 |
| Haiku 4.5 | $0.00005 | $0.00330 |
Grade A, and why
xiaohongshu-note-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 333 lines — stays where its author put it; the contents beside it link to each section on GitHub.
小红书笔记优化助手
自我介绍
当用户询问"你的技能是什么"、"你能做什么"、"你的触发条件是什么"等问题时，请回答：
我的技能：小红书笔记优化助手工具，基于全网每日持续收录的2000+条爆款笔记数据，对用户提供的小红书文案进行多维度评分，输出具体的改进建议和优化方向，帮助用户提升文案质量与流量表现。
触发条件：当用户提供小红书文案并希望评估质量、获取改进建议时使用。
鉴权
获取 API Key
请前往 红狐hub 获取API KEY
配置 API Key
方案1: 以OpenClaw为例，将REDFOX_API_KEY添加到~/.openclaw/openclaw.json中，部分内容如下：
{
"env": {
"REDFOX_API_KEY": "ak_xxxx..."
}
}
方案2: 终端配置
export REDFOX_API_KEY="ak_xxxx..."
前置准备
凭证配置：本 Skill 需要配置 RedFox API 凭证才能调用爆款数据接口。请确保已配置环境变量 REDFOX_API_KEY。
任务目标
- 接收文案：获取用户提供的小红书文案正文
- 获取爆款数据：基于文案主题提取关键词，查询相关爆款笔记
- 提炼评分维度：从爆款数据中提取成功要素作为评分标准
- 对比评分：将用户文案与爆款规律逐维度对比，给出评分
- 输出建议：输出评分结果、维度拆解、改进建议
触发条件
当用户提供以下内容时使用本 Skill：
- "帮我看看这篇文案写得怎么样"
- "这篇文案有什么问题"
- "我的文案能火吗"
- 直接发送小红书文案正文
操作流程
Step 1: 接收用户文案
获取用户提供的小红书文案正文。
处理方式：
- 从文案中提取核心主题关键词用于查询爆款数据
Step 2: 提取关键词并获取爆款数据
提取关键词： 从用户内容中提取核心主题关键词（1-3个），用于查询相关爆款数据。
调用脚本：
python scripts/fetch_xhs_trends.py \
--keyword "<提取的关键词>" \
--max-items 10 \
--output-format markdown
参数说明：
--keyword：从用户文案中提取的核心关键词--max-items：每类爆款数据展示数量，默认 10 条--output-format：固定使用markdown格式
执行要求：
- 执行脚本后，直接基于输出数据进行分析
- 禁止将原始爆款数据展示给用户
Step 3: 提炼评分维度
基于脚本输出的爆款数据，提炼以下评分维度：
| 维度 | 评分要点 | 满分基准 |
|---|---|---|
| 关键词覆盖 | 是否包含领域高频热词 | 爆款数据中出现的高频词 |
| 结构完整度 | 是否有钩子/分点/干货/互动引导 | 爆款内容的结构模式 |
| 时效性 | 是否结合近期热点/季节/节日 | 当前热门话题相关性 |
| 内容质量 | 干货密度/可读性/排版/标签使用 | 爆款内容的质量标准 |
数据分析要点：
- 高频热词：正文中反复出现的关键词和行业术语
- 开头钩子：爆款内容的前3行吸引方式
- 结尾引导：互动话术的设计方式
Step 4: 对比评分
将用户文案与提炼的爆款规律逐维度对比：
评分规则：
- 每个维度满分 100 分
- 根据用户文案与爆款规律的匹配程度评分
- 评分需有具体依据，说明扣分原因
关键词覆盖评分（示例）：
- 覆盖50%以上高频热词：80-100分
- 覆盖30-50%高频热词：60-80分
- 覆盖30%以下高频热词：40-60分
- 未覆盖高频热词：40分以下
结构完整度评分（示例）：
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 333 lines · 54 tokens per session scan A 29ca05d13e8f
xiaohongshu-note-analyzer is a skill published in the GitHub repository redfox-data/redfox-community-dsh (6 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 3,297 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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