xiaohongshu-ops▌
xiangyu-cas/xiaohongshu-ops-skill · updated May 30, 2026
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$22
Openclaw 小红书运营技能(通用版)
目标:构建可复用的“小红书运营”流程,让任何账号类型都能复用同一套动作框架。
适用范围(默认即通用流程)
- 账号定位与内容方向
- 选题产出与争议点挖掘
- 竞品/同类账号对标
- 小红书发布前演练与内容交付
- 发布后快速复盘(互动结构、评论回复、热点追踪)
- Viral Copy 链路(输入 URL,高贴合学习封面/配图、标题、正文并生成可发布近似结构笔记)
将每类账号的行业细节作为“案例模块(case module)”挂载到通用流程中。
常用术语
选题:可发布、可讨论、可转发的内容切入点引流钩子:标题/开头一句用于触发停留与点击结构化输出:标题、正文、互动问句、话题、标签五元组快照:用于验证页面状态的关键证据快照回放:流程失败后重试或改道执行
0) 启动与环境校验(所有任务都遵循)
执行前先按 references/xhs-runtime-rules.md 中“运行规则”执行,优先遵循失败可复用顺序。
- 固定使用内置浏览器 profile:
openclaw,出现通道异常先切回后再重试。 - 若 browser(openclaw-manager)能力处于 disabled/不可用:先执行一次轻量重试(如 status/profiles),仍不可用则进入故障引导,明确告知用户“当前浏览器工具未启用”,并引导用户按文档启用后再继续(参考:
https://docs.openclaw.ai/tools/browser)。 - 以
evaluate为先,关键节点少量snapshot,单步动作最多重试一次。 - 失败后保留已获结果,切稳健路径并汇报。
1) 技能默认行为(所有任务都遵循)
- 先读本技能目录下的
persona.md(小红书平台专用人设/语气/发布与回复风格)。所有对外文案(发帖/评论回复/私信话术)都必须遵循。 - 开始新任务前,先读
knowledge-base/README.md这个总览入口,再按references/xhs-knowledge-base.md的规则检索最近的同类记录;能复用的 pattern 不重复摸索。 - 优先输出可执行的 SOP 而非一次性内容稿
- 语言优先“能对话”而不是“写报告”:短句、口语、站位明确、可引导评论
- 所有输出默认保留“可追问点”,用于评论区继续延展
2) 账号定位(可复用)
每个账号先确认 4 个变量:
- 目标用户:年龄/场景/痛点(如「下班后碎片时间」「追星讨论人群」)
- 内容价值主张:每篇给用户什么(观点、情绪价值、实操建议)
- 差异化角度:同类账号不做什么、你做什么
- 风格规范:语气、长度、冲突边界(避免过激)
输出:
- 人设关键词(3-5)
- 内容支柱(3 个)
- 口头禅/固定句式(2-3 个)
- 不能碰底线(红线)清单(剧透、人身攻击、虚假承诺)
2.5) 账号分析(新增)
按 references/xhs-account-analysis.md 执行。
- 默认采样最近 9-15 篇内容做轻量体检
- 从定位、内容结构、互动转化、辨识度、可持续性 5 个维度判断
- 输出必须包含“最大优势、最大短板、下一步动作”
3) 通用选题与对标流程
A. 平台侧抓取信号(可并行)
- 先在小红书抓同题材高互动内容(点赞/收藏/评论高于近期平均值)
- 记录可复用字段:
title,hook,angle,结构标签,评论信号,互动CTA,标签组 - 汇总前 10-20 条到候选池
A.1 首页推荐流分析(新增)
按 references/xhs-home-feed-analysis.md 执行。
- 先看首页推荐流里“为什么推给你”
- 再提炼可复用的传播钩子、内容结构和选题方向
- 结果优先服务账号定位、选题灵感和后续内容判断
B. 需求侧补充信号(行业/场景)
- 按主题去主流平台/社媒抓“评论区观点分歧”
- 抽取支持/反对/中性观点各一组
- 输出可发文争论点(争议但可控)
C. 形成选题清单(每轮至少 3 条)
每条选题包含:
- 选题标题(20 字内可选)
- 观点标签(支持/反对/中性)
- 预计互动钩子
- 证据来源(哪组高互动数据)
- 风险提示(是否容易踩线)
3.2) 选题灵感(新增)
按 references/xhs-topic-ideation.md 执行。
- 将平台信号、需求信号、账号定位合并成可发布选题
- 默认输出 3-5 条,每条都要带互动钩子和三段式结构
- 产物可直接作为内容生成或 Viral Copy 的前置输入
3.5) 搜索并浏览(新增操作类型)
按 references/xhs-runtime-rules.md 的搜索与评论入口章节执行。
- 只允许从搜索结果页进入帖子;
- 优先通知/回复场景前先对位校验。
- 连续失败回退策略见引用文件。
3.6) Viral Copy(URL → 新笔记)
按 references/xhs-viral-copy-flow.md 执行。
- 输入:目标爆款笔记 URL(可多条)。
- 输出:1 套可发布素材(封面/配图方案 + 标题 + 正文 + 话题)。
- 复刻原则:高贴合主题与结构(标题句式、封面信息层级、正文节奏、互动机制),同时避免逐字照抄与素材侵权。
4) 通用内容模板(小红书)
每次产出至少 2 个备选:
- 标题(争议/立场/反问,≤20字优先)
- 开头钩子(1-2 句)
- 正文(3 段:观点→证据→反方)
- 互动提问(1 句)
- 话题(5-8 个)
- 风险标注(是否剧透 / 引战边界 / 版权风险)
5) 通用发布链路(不发稿)
详细发布执行路径请直接按 references/xhs-publish-flows.md 执行,避免重复维护。
发布前必须满足的核心点:
- 账号先登录创作后台,确认页面在
openclawprofile 可操作。 - 明确发布类型(视频 / 图文 / 长文),三要素:封面、标题、正文。
- 到达“发布”按钮可见处停手,默认不直接点击发布。
- 若涉及截图确认,优先附件形式发送到飞书,并在用户确认后再发布。
6) 评论与回复(轻量)
评论检查与回复统一遵循 references/xhs-comment-ops.md,并结合 examples/reply-examples.md 作文案风格。
- 默认优先走通知页,先对位后输入后发送。
- 默认 one-send-per-turn(如无明确要求不连发)。
- 长度、隐性承诺、风控停损点等风险控制项请以引用文件为准。
6.5) 知识库沉淀(新增)
按 references/xhs-knowledge-base.md 执行。
- 总览入口固定为
knowledge-base/README.md - 细分记录按类型写入
knowledge-base/accounts/、knowledge-base/topics/、knowledge-base/patterns/、knowledge-base/actions/、knowledge-base/reviews/ - 分析优先沉淀
pattern/topic/review - 执行动作优先沉淀
action - 任务结束时至少留下可检索的结论、证据、风险和下一步
7) 失败与修复(必须遵循)
- 自动化失败先重试一次(同策略)
- 仍失败则改道:换到“更稳妥同义路径”
- 不做无效重复动作;保留当前进度可复用,报告一次用户需手动的单一动作
- 若知识库暂时不可写,先返回结构化摘要,任务结束后补记,不阻塞主流程
8) 通用提取示例(Evaluate)
通用字段提取脚本示例见 references/xhs-eval-patterns.md。
9) 具体案例:陪你看剧(保留为特例)
使用方式
本技能主文件保留通用框架;垂直行业经验放在 examples/ 目录,按内容类型选用:
- 先按《通用流程》跑一遍
- 再加载对应案例文件补齐行业特殊动作
当前已可用案例:
examples/drama-watch/case.md(陪你看剧账号)
每个内容类型按目录组织,文件命名可为:
-
examples/<vertical>/<vertical>.md(推荐) -
或
examples/<vertical>/README.md -
examples/lifestyle/(待补充) -
examples/cosmetics/(待补充) -
examples/fitness/(待补充)
实操经验(持续有效)
- 统一规则:所有浏览器操作一律走内置浏览器 profile=
openclaw(除非用户明确要求使用 Chrome 扩展 Relay)。 - 文字配图是稳定写入口,typed text 直接成为封面文案
- 发布话题优先用 UI 选题,不建议纯文本粘贴大量
#话题 evaluate批量改写富文本时,尽量少改版式,避免丢失 topic entity- 关键步骤前保留一次快照,可用于复盘与问题定位
发布按钮可见 ≠ 发布成功;必须明确标注“到发布页停手”- 若出现新类型评论节奏问题,优先减少每小时回复密度而非提高频率
运营成熟路径(可选)
- 标题池:按“站队/反问/冲突”各保留 10 条可复用模板
- 话题池:按账号调性建立常用关键词与同义替换列表
- 复用机制:每次复盘后把可复用表达同步进案例文件
How to use xiaohongshu-ops on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add xiaohongshu-ops
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches xiaohongshu-ops from GitHub repository xiangyu-cas/xiaohongshu-ops-skill and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate xiaohongshu-ops. Access the skill through slash commands (e.g., /xiaohongshu-ops) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★43 reviews- ★★★★★Luis Thomas· Dec 24, 2024
Useful defaults in xiaohongshu-ops — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Carlos Sanchez· Dec 16, 2024
I recommend xiaohongshu-ops for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Dec 8, 2024
Useful defaults in xiaohongshu-ops — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yash Thakker· Nov 27, 2024
xiaohongshu-ops has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sakshi Patil· Nov 23, 2024
Registry listing for xiaohongshu-ops matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Luis Haddad· Nov 15, 2024
xiaohongshu-ops has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Diego Agarwal· Nov 11, 2024
Registry listing for xiaohongshu-ops matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Neel Gupta· Nov 7, 2024
Solid pick for teams standardizing on skills: xiaohongshu-ops is focused, and the summary matches what you get after install.
- ★★★★★Naina Nasser· Oct 26, 2024
xiaohongshu-ops has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Dhruvi Jain· Oct 18, 2024
Solid pick for teams standardizing on skills: xiaohongshu-ops is focused, and the summary matches what you get after install.
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