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-searchgit 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-search)<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/xiaohongshu-search"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/xiaohongshu-search/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-search"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/xiaohongshu-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00061 | $0.07870 |
| Opus 5 | $0.00030 | $0.03935 |
| Sonnet 5 | $0.00012 | $0.01574 |
| Haiku 4.5 | $0.00006 | $0.00787 |
Grade A, and why
xiaohongshu-search 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 7d 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 — 580 lines — stays where its author put it; the contents beside it link to each section on GitHub.
小红书爆款笔记查询
1. 简介
小红书热门笔记搜索工具，支持按关键词搜索小红书热门爆款笔记，并基于相关性、热度、时效三维评分智能排序推荐。同时提供热门笔记推荐和细分赛道引导，助力创作者、品牌方和 MCN 机构发现热门趋势、获取创作灵感。注意：本工具仅在主 Agent 中执行，不派发给子 Agent。
2. 功能特性
- 🔍 关键词智能搜索 — 支持关键词精确搜索、多关键词组合（逗号分隔）、全站热门查询（空关键词）
- 📊 三维评分排序 — 有关键词时按相关性（满分10分）、热度（满分3分）、时效（满分2分）加权计算总分（满分15分），全站热门按互动数排序
- 🧠 精细意图理解 — 优先从用户描述中提取细分方向词，识别泛化词并自动推荐 10 个细分方向
- ⏱️ 灵活时间范围 — 默认查询最近7天，数据不足时自动扩展时间范围（1天→3天→7天→30天），每日早上7点更新
- 🔥 热门笔记推荐 — 结果较少时自动展示近期热门推荐笔记和热门话题标签
- 📈 细分赛道引导 — 每次查询后主动推荐 10 个相关细分方向，帮助用户深入探索
- 🏷️ 拓词推荐 — 脚本返回 relatedSearches 字段，自动展示相关搜索建议
- 📩 定时订阅推送 — 支持创建日历订阅任务，到达设定时间自动推送最新热门笔记
- 📄 HTML 报告生成 — 自动生成
{keyword}_热门数据.html可视化文件 - 🛡️ 强数据说明 — 热门笔记收录标准为互动数1000+，顶部展示数据说明和排序依据
3. 一键安装
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：
{ "env": { "REDFOX_API_KEY": "ak_xxxx..." } }
方案2: 终端配置
export REDFOX_API_KEY="ak_xxxx..."
依赖安装
本 Skill 使用 Python 3 标准库，无需额外安装第三方依赖。确保系统中已安装 Python 3.x 即可。
环境变量配置
| 环境变量 | 说明 | 是否必填 | 获取方式 |
|---|---|---|---|
REDFOX_API_KEY |
红狐数据 API Key | 是 | 红狐hub |
4. 使用指南
⚠️ 核心执行规则（必须遵守）
- 泛化词必须先询问再查询：当识别到泛化词时，绝对禁止直接调用脚本，必须先输出细分词推荐并等待用户选择后再执行查询
- 正确执行顺序：关键词提取 → 判断是否泛化词 → 是泛化词则询问用户 → 用户回复后再调用脚本
- 强制等待规则：输出细分词推荐后，必须停止执行，等待用户下一轮对话回复「拓展」或「不拓展」，不得在同一次对话中继续执行任何脚本调用
常见泛化词： 泛词：抽象层级高、覆盖范围广的概括性词汇，无具体场景/属性修饰，行业分类等，可包含多个子类。特征：①语义上为上位概念（如"美妆"包含"粉底液/口红"；"运动"包含"跑步/瑜伽"；如AI）；②上下文中常搭配"领域""类型"等概括词（如"美妆领域""运动类型"）。
常见具体词： 具体词：抽象层级低、指向明确的实例化词汇，含具体场景/属性修饰，属于某泛词的直接子类。特征：①语义上为下位概念（如"粉底液"是"美妆产品"子类；"生酮饮食"是"饮食方式"子类）；②词语结构多含修饰成分（如"春日"→"春日穿搭"；"生酮"→"生酮饮食"）。
基础使用（3 步完成查询）
Step 1 — 提取关键词：从用户自然语言描述中提取搜索关键词。优先提取细分方向词（含具体场景/属性修饰），而非泛化大类词。
Step 2 — 调用脚本：
python scripts/fetch_xhs_hot_articles.py --keyword <关键词> --start-date <日期>
- 有赛道关键词：
python scripts/fetch_xhs_hot_articles.py --keyword <关键词> --start-date <日期> - 无赛道关键词（查询全站热门）：
python scripts/fetch_xhs_hot_articles.py --keyword "" --start-date <日期> - 多个关键词用逗号分隔：
python scripts/fetch_xhs_hot_articles.py --keyword "减脂餐,职场穿搭,健身" --start-date <日期> - 分页参数：
--page-num 1 --page-size 50
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.
- 7d ago First seen · 580 lines · 61 tokens per session scan A 53fe936b0a95
xiaohongshu-search is a skill published in the GitHub repository redfox-data/redfox-community-dsh (5 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 7,870 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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