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♾️ Free & Open Source 🛡️ Secure & Worry-Free

Import Skills

Composite Most Downloads Most Likes Most Comments Newest
otter1101 otter1101
from GitHub Content & Multimedia
  • 📁 references/
  • 📁 scripts/
  • 📄 .gitignore
  • 📄 install.py
  • 📄 LICENSE
python http 认知层

blogger-distiller

Use when the user wants to analyze or distill a Xiaohongshu blogger/account, benchmark a target creator, or diagnose their own content strategy. Trigger on requests such as “拆解博主”“蒸馏博主”“分析小红书博主”“诊断我的小红书账号”“对标账号”“内容策略分析”“小红书账号分析”. --- # 博主蒸馏器 ## 你是什么 自动化的小红书博主蒸馏工具。**输入一个博主名字，输出两样最终产物：** 1. **HTML 蒸馏报告** — 给人看。浏览器打开，快速理解这个博主的人设、认知层、策略层和内容层。 2. **创作 Skill 文件夹** — 给 AI 用。安装后说"用 XX 风格写一篇笔记"，AI 立刻知道怎么写。 模式 A 用来拆解对标博主（学 TA），模式 B 用来诊断自己的账号（看自己）。 核心理念：**脚本保下限，AI 冲上限。** 脚本负责数据采集和确定性分析，AI 负责蒸馏洞察和生成最终产物。 --- ## 能力范围 爬取目标博主笔记数据（支持 30 / 50 / 80 三档），三层蒸馏产出： ### 三层蒸馏结构 | 层级 | 回答什么 | 举例 | |------|---------|------| | **认知层** | TA 怎么想？ | 核心信念 / 观点张力 / 价值立场 / 思维模式 | | **策略层** | TA 怎么运营？ | 系列规划 / 蹭热点方式 / 运营习惯 / 发布节奏 | | **内容层** | TA 怎么写？ | 标题公式 / 开头模板 / CTA / 视觉风格 / 标签策略 | ### 产出物一：HTML 蒸馏报告（10 个模块） 1. 一眼看清（摘要卡片） 2. 人设拆解 3. 认知层：TA 怎么想 4. 策略层：TA 怎么运营 5. TOP10 爆款拆解 6. 内容公式速查 7. 选题灵感 TOP15 8. 数据面板（基础展开，详细折叠） 9. 发展趋势（附置信度标注） 10. 核心结论 ### 产出物二：创作 Skill 文件夹 - 模式 A：`{博主名}_创作指南.skill/SKILL.md` - 模式 B：`{用户名}_创作基因.skill/SKILL.md` - 8 大章节：使用说明 → 认知层 → 策略层 → 内容层 → 创作禁区 → 对比示例 → 选题灵感 → 局限性+自检清单 ### 分工 **脚本做 30%**（保下限）： - 环境检查、扫码登录、数据采集 - 统计分析（11种标题模式、6类CTA、藏赞比、发布频率） - 认知层粗提取（观点句候选、思维模式统计、价值词） - 数据底稿 + AI 蒸馏任务生成 **AI 做 70%**（冲上限）： - 生成 HTML 蒸馏报告 - 生成创作 Skill 文件夹 - 抽取信念、张力、框架、创作禁区、对比示例 - 因果分析、个性化建议、金句总结 --- ## 前置要求 - 需要本地桌面环境（支持显示图片或打开文件） - 云端/无头服务器暂不支持（无法完成扫码登录） - Python 3.8+（Skill 会自动检测，如未安装会提示） - 网络连接（用于下载 MCP 二进制和爬取小红书数据） ### 代理设置 如需通过代理访问 GitHub 或小红书，设置环境变量： ```bash # Windows $env:HTTP_PROXY="http://127.0.0.1:7890" $env:HTTPS_PROXY="http://127.0.0.1:7890" # macOS/Linux export HTTP_PROXY="http://127.0.0.1:7890" export HTTPS_PROXY="http://127.0.0.1:7890" ``` --- ## 执行流程 ### Phase 0: 环境自动准备 运行 `python scripts/check_env.py` 自动检查并修复以下依赖： 1. **python-docx** — 检测到未安装时自动 `pip install`（沿用现有环境准备逻辑） 2. **xiaohongshu-mcp 二进制** — 检测到未安装时自动从 GitHub Releases 下载最新版到 `~/.xiaohongshu/bin/` 3. **MCP 服务** — 检测到未运行时自动后台启动 4. **小红书登录状态** — 检测到未登录时提示扫码登录 **扫码登录详细流程：** 1. 调用 `check_login_status` 检查登录状态 2. 若已登录 → 跳到

⬇0 ❤6 8 days ago · Uploaded Detail →

Skill File Structure Sample (Reference)

skill-sample/
├─ SKILL.md              ⭐ Required: skill entry doc (purpose / usage / examples / deps)
├─ manifest.sample.json  ⭐ Recommended: machine-readable metadata (index / validation / autofill)
├─ LICENSE.sample        ⭐ Recommended: license & scope (open source / restriction / commercial)
├─ scripts/
│  └─ example-run.py     ✅ Runnable example script for quick verification
├─ assets/
│  ├─ example-formatting-guide.md  🧩 Output conventions: layout / structure / style
│  └─ example-template.tex         🧩 Templates: quickly generate standardized output
└─ references/           🧩 Knowledge base: methods / guides / best practices
   ├─ example-ref-structure.md     🧩 Structure reference
   ├─ example-ref-analysis.md      🧩 Analysis reference
   └─ example-ref-visuals.md       🧩 Visual reference

More Agent Skills specs Anthropic docs: https://agentskills.io/home

SKILL.md Requirements

├─ ⭐ Required: YAML Frontmatter (must be at top)
│  ├─ ⭐ name                 : unique skill name, follow naming convention
│  └─ ⭐ description          : include trigger keywords for matching
│
├─ ✅ Optional: Frontmatter extension fields
│  ├─ ✅ license              : license identifier
│  ├─ ✅ compatibility        : runtime constraints when needed
│  ├─ ✅ metadata             : key-value fields (author/version/source_url...)
│  └─ 🧩 allowed-tools        : tool whitelist (experimental)
│
└─ ✅ Recommended: Markdown body (progressive disclosure)
   ├─ ✅ Overview / Purpose
   ├─ ✅ When to use
   ├─ ✅ Step-by-step
   ├─ ✅ Inputs / Outputs
   ├─ ✅ Examples
   ├─ 🧩 Files & References
   ├─ 🧩 Edge cases
   ├─ 🧩 Troubleshooting
   └─ 🧩 Safety notes

Why SkillWink?

Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.

We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.

Keyword Search Version Updates Multi-Metric Ranking Open Standard Discussion

Quick Start:

Import/download skills (.zip/.skill), then place locally:

~/.claude/skills/ (Claude Code)

~/.codex/skills/ (Codex CLI)

One SKILL.md can be reused across tools.

FAQ

Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.

1. What are Agent Skills?

A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.

Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.

2. How do Skills work?

Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.

This keeps agents lightweight while preserving enough context for complex tasks.

3. How can I quickly find the right skill?

Use these three together:

  • Semantic search: describe your goal in natural language.
  • Multi-filtering: category/tag/author/language/license.
  • Sort by downloads/likes/comments/updated to find higher-quality skills.

4. Which import methods are supported?

  • Upload archive: .zip / .skill (recommended)
  • Upload skills folder
  • Import from GitHub repository

Note: file size for all methods should be within 10MB.

5. How to use in Claude / Codex?

Typical paths (may vary by local setup):

  • Claude Code：~/.claude/skills/
  • Codex CLI：~/.codex/skills/

One SKILL.md can usually be reused across tools.

6. Can one skill be shared across tools?

Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.

Example: retrieval + writing + automation scripts as one workflow.

7. Are these skills safe to use?

Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.

8. Why does it not work after import?

Most common reasons:

  • Wrong folder path or nested one level too deep
  • Invalid/incomplete SKILL.md fields or format
  • Dependencies missing (Python/Node/CLI)
  • Tool has not reloaded skills yet

9. Does SkillWink include duplicates/low-quality skills?

We try to avoid that. Use ranking + comments to surface better skills:

  • Duplicate skills: compare differences (speed/stability/focus)
  • Low quality skills: regularly cleaned up