Agent skill

Xhs Skill

by aAAaqwq in aAAaqwq/AGI-Super-Team

小红书(创作者中心)登录拿 cookies、发布笔记、导出数据的单一入口技能(浏览器交互委托 agent-browser-stealth)

MITAuto-check passedProductivity & Automation

Install Xhs Skill

skills CLI
$ npx skills add aAAaqwq/AGI-Super-Team --skill xhs-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aAAaqwq/AGI-Super-Team xhs-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/xhs-skill .claude/skills/xhs-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
xhs-skill
GitHub stars
105
Used in
1 other repo
Token cost
~3.2k tokens
SKILL.md length
624 words
Files
12 (incl. scripts)
Skills in repo
167
Repo updated
First seen
Licence
MIT

At a glance

小红书(创作者中心)登录拿 cookies、发布笔记、导出数据的单一入口技能(浏览器交互委托 agent-browser-stealth)

  • Works in 2 steps: 让 agent-browser-stealth 截图保存二维码(PNG)到… → (可选)用本地 CLI 解码二维码文本并打印 ASCII 二维码
  • Tasks that involve Browser automation
  • SKILL.md covers 安装, 目录约定(本机), A. 登录(扫码)并保存 cookies and A1. 防封/限流运行规范(强制), plus 4 more sections
  • Runs JavaScript scripts from its folder; calls node, npm and git; reaches creator.xiaohongshu.com

What it does

Xhs Skill is an agent skill from aAAaqwq/AGI-Super-Team. 小红书(创作者中心)登录拿 cookies、发布笔记、导出数据的单一入口技能(浏览器交互委托 agent-browser-stealth)

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts (for example `agents/openai.yaml`, `config/review_policy.json` and `config/review_taxonomy.json`).

It sits in Productivity & Automation, covering Browser automation. It works with Xiaohongshu. The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.

When your agent uses it

  • Tasks that involve Browser automation

Example prompts

  • “/xhs-skill”

Requirements

  • Node.js

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. 让 agent-browser-stealth 截图保存二维码(PNG)到 data/xhs_login_qr.png
  2. (可选)用本地 CLI 解码二维码文本并打印 ASCII 二维码

What it can do on your machine

Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • node
    • npm
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • creator.xiaohongshu.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Xhs Skill loads about 3.2k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 624 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 624 words, ~3,181 tokens.

Download SKILL.mdSave it as .claude/skills/xhs-skill/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
xhs-skill
description
小红书(创作者中心)登录拿 cookies、发布笔记、导出数据的单一入口技能(浏览器交互委托 agent-browser-stealth)

本技能是 xhs-* 的合并版,目标是让用户只需要 clawhub install xhs-skill 一次即可开始使用。

约束:

  • 所有浏览器交互(打开页面/点击/输入/上传/截图/登录/导出)全部委托 agent-browser-stealth。
  • 禁止在本仓库编写/维护发布编排脚本(如 publish_from_payload);发布动作必须在会话中由 agent-browser-stealth 执行。
  • 禁止使用 agent-browser(旧通道禁用,统一使用 agent-browser-stealth)。
  • 所有敏感数据(cookies、导出文件、截图)只落地在本机 data/ 目录,不要粘贴到聊天里。

执行硬约束(稳定性):

  • 同一 agent-browser-stealth session 禁止并发操作(串行执行),否则容易触发 os error 35 假失败。
  • snapshot 的 ref 会漂移:关键动作前后必须重抓 snapshot -i,并用 placeholder/role/text 做二次定位兜底。
  • 扫码不等于登录成功;必须做后验校验(见下方 A 节“登录成功判定”)。

安装

bash
clawhub install xhs-skill
cd skills/xhs-skill
npm i

说明:npm i 仅用于本技能自带的本地 CLI(二维码解码、cookies 工具)。如果你不需要解码二维码/转换 cookies,也可以只用 agent-browser-stealth 完成扫码与导出。

目录约定(本机)

建议在你运行命令的工作目录下准备:

  • data/xhs_login_qr.png:登录页二维码截图(PNG)
  • data/raw_cookies.json:导出的原始 cookies(JSON)
  • data/xhs_cookies.json:归一化后的 cookies(JSON)
  • data/exports/<YYYY-MM-DD>/:导出数据(CSV/XLSX/截图)
  • data/assets/<YYYY-MM-DD>/:发布笔记用的图标/配图素材与来源记录
bash
mkdir -p data

A. 登录(扫码)并保存 cookies

目标:登录小红书创作者中心并导出 cookies,避免频繁重复登录。

  1. 用 agent-browser-stealth 打开登录页:
  • https://creator.xiaohongshu.com/login
  • 若默认展示「手机号/验证码登录」,点击「扫码」切换到二维码视图
  1. 让 agent-browser-stealth 截图保存二维码(PNG)到 data/xhs_login_qr.png

  2. (可选)用本地 CLI 解码二维码文本并打印 ASCII 二维码:

bash
node ./bin/xhs-skill.mjs qr show --in ./data/xhs_login_qr.png

OpenClaw 回传规范(强制):

  • 禁止只回传文件路径(例如仅说 data/xhs_login_qr.png)。
  • 必须先执行 node ./bin/xhs-skill.mjs qr show --in ./data/xhs_login_qr.png,然后把输出的二维码文本 + ASCII 二维码直接发给用户。
  • 若会话支持图片渲染,再附上二维码截图绝对路径(或图片附件)作为补充。
  • 发完二维码后必须暂停,等待用户确认“已扫码”再继续 cookies 导出。

推荐回传模板:

text
请用小红书 App 扫这个二维码登录。
二维码文本: <qr_text>
<ASCII QR>
  1. 用小红书 App 扫码完成登录后,导出 cookies 到 data/raw_cookies.json(不走 DevTools):
bash
agent-browser-stealth cookies --json > ./data/raw_cookies.json
  1. 归一化 cookies 并保存到 data/xhs_cookies.json:
bash
node ./bin/xhs-skill.mjs cookies normalize --in ./data/raw_cookies.json --out ./data/xhs_cookies.json
node ./bin/xhs-skill.mjs cookies status --in ./data/xhs_cookies.json

5.1 推荐用脚本做后验校验(可执行门禁):

bash
# 例:先让 agent-browser-stealth 记录当前 URL 与后台探测后的 URL
CURRENT_URL="$(agent-browser-stealth get url)"
agent-browser-stealth open https://creator.xiaohongshu.com/creator/home
PROBE_FINAL_URL="$(agent-browser-stealth get url)"

node ./scripts/verify_login.mjs \
  --cookies ./data/xhs_cookies.json \
  --current-url "$CURRENT_URL" \
  --probe-final-url "$PROBE_FINAL_URL" \
  --json

登录成功判定(强制):

  • 必须同时满足以下 2 条才可回报“登录完成”(web_session 不再作为硬依赖):
  • 当前 URL 已离开 /login
  • 可访问创作者后台页面,且不会 401/回跳登录
  • 加分项:cookies 中存在“session-like cookie”(例如 web_session,或 cookie 名含 session)。没有也可能可用,但稳定性更差。
  • 任一强制条件不满足,必须回报“登录失败/未完成”,并重试登录流程;禁止误报成功。

登录结果输出契约(JSON):

json
{
  "task": "xhs_login",
  "ok": true,
  "checks": {
    "left_login": true,
    "backend_not_rejected": true,
    "has_session_like_cookie": true
  },
  "artifacts": {
    "qr_png": "data/xhs_login_qr.png",
    "raw_cookies": "data/raw_cookies.json",
    "normalized_cookies": "data/xhs_cookies.json"
  }
}

失败时 ok=false,并给出失败项(例如仍在 /login、或 probe 回跳),禁止输出“已完成”。

  1. (可选)生成 Cookie: header:
bash
node ./bin/xhs-skill.mjs cookies to-header --in ./data/xhs_cookies.json

失败回退:

  • 二维码解码失败:通常是没有切到扫码视图或二维码太小,让 agent-browser-stealth 放大后重新截图(仍为 PNG)。
  • cookies 归一化失败:保留原始 data/raw_cookies.json,后续再扩展兼容分支。

A1. 防封/限流运行规范(强制)

核心结论:小红书风控主要看“节奏 + 指纹 + 行为 + IP + 账号权重”。工具本身不是主因,使用方式才是主因。

强制策略:

  1. 真人节奏:
  • 禁止连续无停顿点击/填写;关键动作之间必须随机停顿(建议 1.2s~7s)。
  • 输入优先 type --delay(逐字),避免全量瞬时 fill。
  1. 固定指纹:
  • 运行发布流程时优先固定 --profile,并启用 --headed。
  • 推荐同一账号长期复用同一个 profile 目录,不要每次新建临时环境。
  1. 发布频率门禁:
  • 同一 profile 默认 24h <= 3 篇。
  • 两次发布最小间隔默认 30 分钟。
  • 命中门禁必须中止,不允许强发。
  1. 发布前预热行为:
  • 先做一次短时正常浏览(首页/创作者后台停留 + 滚动),再进入发布页。
  • 禁止“打开页面后立刻提交”。
  1. 网络与设备:
  • 禁止机房 IP / 高频切换代理。
  • 优先家庭网络或手机热点;同账号尽量保持设备/IP 稳定。
  1. 被限流后的处理:
  • 限流:停自动化,回归手动正常使用 3~7 天。
  • 封号:仅能申诉;换号时要同时更换 profile + IP + 设备环境。

B. 发布笔记(图文/视频)

输入(用户提供):

  • 笔记类型:图文 或 视频
  • 标题、正文、标签(必填)
  • 话题(必填;做热点发布时必须是“今天热点”)
  • 图片/视频路径(本机绝对路径优先)
  • 图标/配图需求(可选):关键词、风格(扁平/拟物/线性)、主色、是否透明背景
  • 热点来源(必填):来源名、来源 URL、来源日期(YYYY-MM-DD)

发布硬门禁(强制):

  1. 先把发布素材整理为 data/publish_payload.json(示例):
json
{
  "topic": "今日热点:xxxx",
  "source": {
    "name": "央视新闻",
    "url": "https://example.com/news",
    "date": "2026-02-12",
    "evidence_snippet": "2月12日该媒体报道提到:......",
    "key_facts": ["关键事实1(含日期/数字)", "关键事实2(含日期/数字)"]
  },
  "post": {
    "title": "20字内标题示例",
    "body": "不少于 80 字的正文......",
    "tags": ["#热点", "#今日新闻", "#小红书运营"],
    "real_topics": ["#人工智能", "#AI资讯", "#科技观察"],
    "media": ["/abs/path/cover.png", "/abs/path/card_1.png"]
  }
}
  1. 发布前必须执行校验脚本:
bash
# 普通模式
node ./scripts/verify_publish_payload.mjs --in ./data/publish_payload.json --policy ./config/verify_publish_policy.json --tag-registry ./data/tag_registry.json --min-registry-tags 12 --require-source-evidence on --strict-anti-ai on --json

# 今天热点模式(强制 source.date = 今天)
node ./scripts/verify_publish_payload.mjs --in ./data/publish_payload.json --policy ./config/verify_publish_policy.json --tag-registry ./data/tag_registry.json --min-registry-tags 12 --require-source-evidence on --strict-anti-ai on --mode hot --json
  1. 发布前必须执行内容审核脚本(分层规则 + AI):
bash
node ./scripts/review_publish_payload.mjs --in ./data/publish_payload.json --policy ./config/review_policy.json --taxonomy ./config/review_taxonomy.json --ai-provider auto --require-ai off --mode hot --json
  1. 只有当校验和审核结果都 ok=true 才允许进入发布页点击“发布/提交”。 校验策略在 ./config/verify_publish_policy.json,审核策略在 ./config/review_policy.json,分层风险路径在 ./config/review_taxonomy.json。
  2. 任一门禁失败必须中止流程并提示补齐,禁止“只传截图直接发”。

禁止链接(强制):

  • 标题/正文/标签里禁止出现任何链接或域名形态(http/https、www.、xxx.com/.cn/...)。否则有封禁风险。
  • 如果内容生成遇到困难或校验不通过:宁可中止,不要“随便发一条”。

反 AI 识别与真实标签(强制):

  • 不承诺“100% 不被识别为 AI”;目标是显著降低风险。
  • 正文必须有“个人视角 + 具体事实信号(数字/日期/来源提及)”,并规避模板腔。
  • 发布前必须通过 review_publish_payload 审核门禁,要求 decision=pass,并输出 risk_path、证据和 review_queue 供复核。
  • source.evidence_snippet 与 source.key_facts 必填,且能回溯到来源事实。
  • 标签与 post.real_topics 都必须来自真实话题池 data/tag_registry.json,禁止自造标签。
  • 禁止自动把 #标签 拼进正文冒充话题。
  • 发布前必须在小红书发布页手动选择至少 3 个真实话题,然后由 agent-browser-stealth 执行最终点击发布。

示例:准备真实标签池(建议每天更新):

bash
cat > ./data/tag_registry.json <<'JSON'
{
  "updated_at": "2026-02-24",
  "source": {
    "platform": "xiaohongshu",
    "method": "manual_from_publish_topic_picker",
    "url": "https://creator.xiaohongshu.com/creator/publish"
  },
  "tags": ["#AI热点", "#人工智能", "#行业观察", "#科技新闻", "#AI资讯", "#科技观察"]
}
JSON

发布执行方式(唯一):

  • 本仓库只负责“数据准备 + 门禁校验 + 审核校验”;不再提供发布自动化脚本。
  • 浏览器动作必须由 agent-browser-stealth 串行执行:预检 -> 填充 -> 读回校验 -> 发布 -> 回查。
  • 若任一门禁失败(verify/review 非 ok=true),必须停止在“发布前”,禁止继续点击提交。

P0:发布编排器(流程编排,不是仓库脚本):

  1. 预检:
  • 入口路由固定从 https://creator.xiaohongshu.com/publish/publish 进入;禁止把 /creator/* 作为首入口。
  • 若被跳到 https://creator.xiaohongshu.com/new/home(“你访问的页面不见了”),立即回到 /publish/publish 重试。
  • 进入发布页后先切到“图文”模式,再上传图片;未切图文不进入后续步骤。
  1. 填充:
  • 写标题、正文、标签/话题、可见性。
  1. 读回校验:
  • 校验通过才允许点击发布。
  1. 发布:
  • 点击发布后等待页面状态稳定并记录 URL。
  1. 回查:
  • 先检查 URL 参数包含 published=true;
  • 再从页面菜单进入“笔记管理”做二次确认,不允许硬编码管理页直链回查。

P0:路由与状态稳定性(强制):

  • 稳定入口只认 /publish/publish;其他页面只作为中转,不作为成功判定依据。
  • “发布页可用”不等于“管理页可用”:发布后必须菜单跳转二次查验。
  • 若发布页元素未出现,先检查是否处于“图文模式 + 图片已上传”状态,再判断失败。

P0:选择器双通道(强制):

  • 第一通道(默认):语义定位(placeholder + role + 可见性 + 附近文案)。
  • 第二通道(兜底):DOM 结构线索定位(例如标题输入框 placeholder 语义 + 正文编辑器 tiptap/ProseMirror 语义类名)。
  • 禁止只依赖 snapshot ref 或 @e1/@e2 序号;每个关键动作前后都要 snapshot -i 二次确认。
  • DOM 兜底只作为会话级临时手段,命中后仍需“读回校验”确认字段正确,不把脆弱 selector 当硬依赖。

P0:写入可靠性(强制):

  • 标题字段必须满足:单行、可见、可编辑、placeholder 命中“标题”语义。
  • 正文字段必须满足:多行或 contenteditable、可见、可编辑、placeholder/附近文本命中“正文/内容”语义。
  • 写入后必须做“双向读回校验”:同时读取标题和正文,计算 title_len 与 body_len。
  • 错位判定:若 title_len > 20 且 body_len < 80,或标题命中长段正文特征(大量换行/句号),判定为写入错位。
  • 错位自愈:自动执行“交换重写”一次(清空标题与正文 -> 标题写短标题 -> 正文写正文 -> 读回再校验);仍失败则中止并回报失败,不允许继续提交。
  • 强制规则:标题禁止包含 # 标签、长段正文、链接;标签必须通过小红书发布页“标签/话题交互”选择,不把标签文本塞进标题。

P0:草稿确认闭环(强制):

  1. 点击“暂存离开”后,必须等待并验证“保存成功/已保存草稿”类 toast。
  2. 进入草稿列表,验证出现“新草稿条目”。
  3. 新条目校验最少包含:
Show full SKILL.md (247 more words)Show less
  • 标题前缀匹配本次标题;
  • 时间戳在本次运行窗口内(建议 2 分钟内);
  • 打开草稿后读回 title/body/media/tags 仍满足门禁。
  1. 任一校验失败判定为“草稿保存失败”,允许重试 1 次;重试后仍失败则中止流程。

P0:图片预处理(无脚本版):

  • 不新增仓库脚本;统一采用“发布前本地预处理 + 读回尺寸确认”。
  • 推荐目标尺寸:1242x1660(3:4 竖版)。
  • 可选命令(单次执行,不落仓库脚本):
bash
# macOS: 先居中裁剪再缩放到 1242x1660(按需替换输入输出路径)
sips -c 1660 1242 ./data/assets/in.png --out ./data/assets/out_1242x1660.png
  • 上传后必须在发布页确认缩略图比例正常;若拉伸/裁切异常,先替换素材再继续。

P0:发布前硬校验(强制):

  • 标题长度 <= 20。
  • 正文长度 >= 80。
  • 已上传图片(图文至少 1 张,且可见缩略图)。
  • 已选择真实话题 >= 3(通过小红书话题交互选择,不是正文拼接)。
  • 标题/正文/标签无链接词(http、https、www.、域名形态)。
  • 任一不满足直接中止,不允许“先发再修”。

P0:发布后双重确认(强制):

  1. 第一重:发布后 URL 含 published=true。
  2. 第二重:从发布页菜单进入“笔记管理”,确认列表出现新笔记(标题前缀 + 时间窗口)。
  3. 管理页若被重定向或不可达,判定“回查未完成”,记录 run_log 并提示人工复核。

P1:热点到 payload 半自动(无脚本版):

  • 不新增 newsnow -> payload 代码生成器;改为会话模板填充。
  • 采集热点后,按以下模板生成 data/publish_payload.json,人工只改“观点段”:
json
{
  "topic": "今日热点:<主题>",
  "source": {
    "name": "<来源名>",
    "url": "<来源URL>",
    "date": "YYYY-MM-DD",
    "evidence_snippet": "<原文证据摘录>",
    "key_facts": ["<事实1:含日期/数字>", "<事实2:含日期/数字>"]
  },
  "post": {
    "title": "<8-20字标题,不含标签>",
    "body": "<观点段+事实段,不少于80字>",
    "tags": ["#标签1", "#标签2", "#标签3"],
    "real_topics": ["#真实话题1", "#真实话题2", "#真实话题3"],
    "media": ["/abs/path/1.png"]
  }
}

P1:标签/话题池维护(无脚本版):

  • 每天第一次发布前,手动刷新一次 data/tag_registry.json(从小红书发布页话题选择器抄录)。
  • 若当天未刷新,流程必须回报风险提示并建议先刷新后再发布。
  • 门禁保持不变:tags 与 real_topics 都必须命中 tag_registry。

P1:流程可观测(无脚本版):

  • 每次运行结束都产出 data/run_log/<YYYY-MM-DD_HH-mm-ss>.json(手工写文件即可,不新增脚本)。
  • 建议字段:steps、durations_ms、failed_step、error_message、screenshots、result_url、draft_check、editor_check、route_check、post_publish_check。

P1:固定模板(强烈建议):

  • 固定标题模板:[主题词]+[观点/结论],目标 1218 字,留 28 字缓冲避免超长。
  • 固定正文模板:开场观点 -> 事实1 -> 事实2 -> 个人判断 -> 行动建议,默认 >120 字。
  • 固定标签与话题池:仅从 data/tag_registry.json 选取,避免临场造词导致门禁失败。

P2:回归用例(每日 smoke,手工执行):

  • 场景 1:仅存草稿(不发布)。
  • 场景 2:草稿后二次编辑再存草稿。
  • 场景 3:正式发布(通过全部门禁)。
  • 每个场景都输出一份 run_log,用于对比“定位稳定性/错位率”。

流程(浏览器侧全部由 agent-browser-stealth 完成):

  1. 确保已登录(先完成上面的 A,或已有有效登录态)。
  2. 准备并校验 data/publish_payload.json(必须 ok=true)。
  3. 打开 https://creator.xiaohongshu.com/publish/publish,先 snapshot -i 获取最新结构。
  4. 切图文模式并上传媒体(确认缩略图比例与数量)。
  5. 用“语义定位优先 + DOM 兜底”填写标题与正文,写入后执行“双向读回校验 + 错位自愈”。
  6. 通过小红书标签交互选择标签与真实话题(至少 3 个),不要把标签写进标题。
  7. 执行发布前硬校验(标题、正文、图片、话题、无链接词)。
  8. 点击“暂存离开”并执行草稿闭环校验(toast + 列表新条目 + 读回)。
  9. 点击“发布/提交”前暂停,要求用户确认最终预览。
  10. 发布后执行双重确认(published=true + 菜单进入笔记管理二次查验),并写入 run_log。

发布结果输出契约(JSON):

json
{
  "task": "xhs_publish",
  "ok": true,
  "result_url": "https://creator.xiaohongshu.com/....",
  "content_checks": {
    "title_len": 18,
    "body_len": 136,
    "tag_count": 3,
    "real_topic_count": 3,
    "editor_alignment_ok": true,
    "draft_saved_ok": true,
    "publish_precheck_ok": true,
    "published_param_ok": true,
    "manage_menu_check_ok": true,
    "topic": "今日热点:xxxx",
    "source_date": "2026-02-12"
  },
  "artifacts": {
    "payload_json": "data/publish_payload.json",
    "media_inputs": ["..."],
    "run_log_json": "data/run_log/2026-02-27_14-36-00.json",
    "error_screenshot": null
  }
}

发布失败时 ok=false,并返回 error_message、error_screenshot 路径、未通过的 missing_checks 与 failed_stage(preflight/fill/readback/publish/postcheck)。

C. 导出创作者中心数据(CSV/XLSX 或截图)

目标:把创作者中心关键数据导出到 data/exports/<YYYY-MM-DD>/,用于后续分析。

  1. 确认已登录。
  2. 用 agent-browser-stealth 进入创作者中心的常用分析页(仪表盘/内容分析/粉丝分析)。
  3. 每个页面:
  • 优先使用页面自带导出(如有)到 data/exports/<date>/
  • 无导出时:保存关键区块截图到同目录
  1. 记录:导出时间范围、口径说明、页面 URL。

本地 CLI(本技能自带)

命令:

  • node ./bin/xhs-skill.mjs qr show --in <pngPath>
  • node ./bin/xhs-skill.mjs cookies normalize --in <jsonPath> --out <outPath>
  • node ./bin/xhs-skill.mjs cookies status --in <cookiesJsonPath>
  • node ./bin/xhs-skill.mjs cookies to-header --in <cookiesJsonPath>
  • node ./scripts/verify_publish_payload.mjs --in <payloadJsonPath> --policy ./config/verify_publish_policy.json --tag-registry ./data/tag_registry.json --min-registry-tags 12 --require-source-evidence on --strict-anti-ai on [--mode hot]
  • node ./scripts/review_publish_payload.mjs --in <payloadJsonPath> --policy ./config/review_policy.json --taxonomy ./config/review_taxonomy.json --ai-provider auto --require-ai off [--mode hot]

D. 轻量发版流程(维护者)

  1. 先跑本地门禁:
  • npm run check:constraints
  • npm test
  1. 查看改动只包含预期文件:git status --short
  2. 用中文 Conventional Commit 提交(示例):
  • docs(skill): 补充发版前快速自检清单
  1. 发布到 ClawHub(patch):
  • clawhub sync --all --bump patch --changelog "docs: 补充发版前快速自检清单"

© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (scripts) in skills/xhs-skill of aAAaqwq/AGI-Super-Team.

  • SKILL.md
  • agents/openai.yaml
  • bin/xhs-skill.mjs
  • cli.mjs
  • config/review_policy.json
  • config/review_taxonomy.json
  • config/verify_publish_policy.json
  • package-lock.json
  • package.json
  • scripts/review_publish_payload.mjs
  • scripts/verify_login.mjs
  • scripts/verify_publish_payload.mjs

Open the folder on GitHubat commit 7cefd81

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in aAAaqwq/AGI-Super-Team, which our catalogue first saw on October 9, 2026.

Compare with similar skills

Xhs Skill next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Xhs CLIjackwener/xhs-cli666—~1.1kAutomated safety check: WarnApache-2.0
Xiaohongshu HubOpenMinis/MinisSkills446—~2.7kAutomated safety check: PassMIT
bb-browser Site Commands for OpenClawepiral/bb-browser6.2k—~1kAutomated safety check: PassMIT
Dev-Browser CLI AutomationSawyerHood/dev-browser6.7k1 repos~455Automated safety check: PassMIT

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Works with

Questions about Xhs Skill

What does Xhs Skill do?

小红书(创作者中心)登录拿 cookies、发布笔记、导出数据的单一入口技能(浏览器交互委托 agent-browser-stealth). Xhs Skill is an agent skill from aAAaqwq/AGI-Super-Team.

When should I use Xhs Skill?

Xhs Skill fits situations like: tasks that involve Browser automation.

How do I install Xhs Skill in Claude Code?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill xhs-skill -a claude-code`. Or copy the skill folder (skills/xhs-skill in aAAaqwq/AGI-Super-Team) into .claude/skills/xhs-skill in your project. Claude Code loads it when a task matches its description.

How do I install Xhs Skill in Codex?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill xhs-skill -a codex`. Or copy the skill folder (skills/xhs-skill in aAAaqwq/AGI-Super-Team) into .agents/skills/xhs-skill in your project. Codex loads it when a task matches its description.

Can I use Xhs Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aAAaqwq/AGI-Super-Team --skill xhs-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/xhs-skill, .gemini/skills/xhs-skill, .github/skills/xhs-skill and .opencode/skills/xhs-skill in your project.

What does Xhs Skill need to run?

Going by SKILL.md and its folder, Xhs Skill needs JavaScript for the scripts in its folder and the command-line tools its instructions call (node, npm and git). Our summary lists: Node.js.

Does Xhs Skill access the network?

SKILL.md names 1 domain. In commands or code: creator.xiaohongshu.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Xhs Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Xhs Skill use?

Xhs Skill is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Xhs Skill use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Xhs Skill?

Skills that share tags, products or a category with Xhs Skill: Xiaohongshu Content Research (jumodada/Drissionpage-MCP-Server, 487 stars), Xhs CLI (jackwener/xhs-cli, 666 stars), Xiaohongshu Hub (OpenMinis/MinisSkills, 446 stars) and bb-browser Site Commands for OpenClaw (epiral/bb-browser, 6.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Xhs Skill?

aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.

Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.