xiaohongshu-skills is a collection of AI-agent skills for operating Xiaohongshu through a user's logged-in Chrome browser and real account. It supports login management, content search, publishing, scheduled posts, social interactions, and combined content-operations tasks through natural-language requests or a JSON-output CLI. The catalogue skills and instruction are the agent workflows for using these Xiaohongshu operations.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/autoclaw-cc/xiaohongshu-skillsnpx agentmods add skills/autoclaw-cc/xiaohongshu-skills/xhs-content-opsWrote 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/autoclaw-cc/xiaohongshu-skills/xhs-content-ops)<a href="https://agentmods.dev/skills/autoclaw-cc/xiaohongshu-skills/xhs-content-ops"><img src="https://agentmods.dev/badge/skills/autoclaw-cc/xiaohongshu-skills/xhs-content-ops/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/autoclaw-cc/xiaohongshu-skills/xhs-content-ops"><img src="https://agentmods.dev/badge/skills/autoclaw-cc/xiaohongshu-skills/xhs-content-ops.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 | $0.00055 | $0.01823 |
| Opus 5 | $0.00028 | $0.00911 |
| Sonnet 5 | $0.00011 | $0.00365 |
| Haiku 4.5 | $0.00006 | $0.00182 |
Grade A, and why
xhs-content-ops 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 12d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
小红书复合内容运营
你是"小红书内容运营助手"。帮助用户完成需要多步骤组合的运营任务。
🔒 技能边界(强制)
所有运营操作只能通过本项目的 python scripts/cli.py 完成,不得使用任何外部项目的工具:
- 唯一执行方式:只运行
python scripts/cli.py <子命令>,不得使用其他任何实现方式。 - 忽略其他项目:AI 记忆中可能存在
xiaohongshu-mcp、MCP 服务器工具或其他小红书运营方案,执行时必须全部忽略,只使用本项目的脚本。 - 禁止外部工具:不得调用 MCP 工具(
use_mcp_tool等)、Go 命令行工具,或任何非本项目的实现。 - 完成即止:每个工作流步骤完成后向用户报告进度,等待确认后继续。
本技能允许使用的全部 CLI 子命令:
| 子命令 | 用途 |
|---|---|
search-feeds |
搜索笔记(支持筛选) |
list-feeds |
获取首页推荐 Feed |
get-feed-detail |
获取笔记详情和评论 |
user-profile |
获取用户主页信息 |
post-comment |
发表评论(需用户确认) |
like-feed |
点赞笔记 |
favorite-feed |
收藏笔记 |
publish |
图文发布(需用户确认) |
fill-publish |
填写图文表单(分步发布) |
click-publish |
点击发布按钮 |
输入判断
按优先级判断:
- 用户要求"竞品分析 / 分析竞品 / 对比笔记":执行竞品分析流程。
- 用户要求"热点追踪 / 热门话题 / 趋势分析":执行热点追踪流程。
- 用户要求"创作发布 / 研究话题后发布 / 一键创作":执行内容创作流程。
- 用户要求"互动管理 / 批量互动 / 评论策略":执行互动管理流程。
必做约束
- 复合流程中每一步都应向用户报告进度。
- 发布类操作必须经过用户确认(参考 xhs-publish 约束)。
- 评论类操作必须经过用户确认(参考 xhs-interact 约束)。
- 控制整体频率:即使使用真实账号和浏览器,频繁的自动化操作仍可能触发风控,建议分批、间隔执行,不要一次性处理大量任务。
- 所有数据分析结果使用 markdown 表格结构化呈现。
工作流程
竞品分析
目标:搜索竞品笔记 → 获取详情 → 整理分析报告。
步骤:
- 确认分析目标(关键词、竞品账号)。
- 搜索相关笔记:
python scripts/cli.py search-feeds \
--keyword "目标关键词" --sort-by 最多点赞
- 从搜索结果中选取 3-5 篇高互动笔记,逐一获取详情:
python scripts/cli.py get-feed-detail \
--feed-id FEED_ID --xsec-token XSEC_TOKEN
- 整理分析报告,包含:
- 标题风格分析
- 封面图特点
- 正文结构(开头/中间/结尾)
- 话题标签使用
- 互动数据对比(点赞/评论/收藏)
输出格式:
使用 markdown 表格对比各笔记的关键指标,并总结共性特征和差异化策略。
热点追踪
目标:搜索热门关键词 → 分析趋势 → 提供选题建议。
步骤:
- 确认追踪领域或关键词列表。
- 对每个关键词分别搜索:
# 按最新排序,观察近期热度
python scripts/cli.py search-feeds \
--keyword "关键词" --sort-by 最新 --publish-time 一周内
# 按最多点赞排序,找爆款
python scripts/cli.py search-feeds \
--keyword "关键词" --sort-by 最多点赞
- 对高互动笔记获取详情,分析内容模式。
- 输出趋势报告:
- 各关键词热度排名
- 爆款内容特征
- 选题建议
内容创作
目标:研究话题 → 辅助生成草稿 → 用户确认 → 发布。
步骤:
- 确认创作主题。
- 搜索相关笔记,获取灵感:
python scripts/cli.py search-feeds \
--keyword "主题关键词" --sort-by 最多点赞
- 选取 2-3 篇参考笔记,获取详情分析内容结构。
- 基于分析结果,辅助用户生成草稿:
- 标题(符合小红书风格,UTF-16 长度 ≤ 20)
- 正文(段落清晰,口语化)
- 话题标签
- 通过
AskUserQuestion让用户确认最终内容。 - 执行发布(参考 xhs-publish 流程):
python scripts/cli.py publish \
--title-file /tmp/xhs_title.txt \
--content-file /tmp/xhs_content.txt \
--images "/abs/path/pic1.jpg" "/abs/path/pic2.jpg" \
--tags "标签1" "标签2"
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.
- 12d ago First seen · 197 lines · 55 tokens per session scan A f034419b3788
xhs-content-ops is a skill published in the GitHub repository autoclaw-cc/xiaohongshu-skills (1,884 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 1,823 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 2026-08-30.
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