Add proper Tracey spec annotations to code, find requirements, and check coverage. Use when working with projects that have Tracey configuration (.config/tracey/config.styx), when adding spec references to code, or when checking requirement coverage.
Battle-tested Playwright patterns for E2E, API, component, visual, accessibility, and security testing. Covers locators, fixtures, POM, network mocking, auth flows, debugging, CI/CD (GitHub Actions, GitLab, CircleCI, Azure, Jenkins), framework recipes (React, Next.js, Vue, Angular), and migration guides from Cypress/Selenium. TypeScript and JavaScript.
CONTRIBUTOR TOOL - Track CC changelog, extract new versions since last check, analyze impact on plugin (breaking changes, opportunities, deprecations). Run periodically or before releases. NOT part of the distributed plugin.
使用 Python + UV 读写哔哩哔哩（B 站）数据的技能，依赖 bilibili-api-python + aiohttp， 通过 browser_use get_cookies 自动获取 Cookie 完成认证，无需手动复制。 支持视频详情/字幕/AI总结/评论、用户主页、搜索、热门/排行榜、关注动态 Feed、 收藏夹、稍后再看、观看历史、互动操作（点赞/投币/三连）、动态发布与删除等。 当用户提到"B站"、"哔哩哔哩"、"bilibili"、"B站视频"、"B站热门"、"bilibili-hub"、 "获取B站数据"、"B站字幕"、"B站评论"、"B站收藏"、"B站动态"， 或任何需要以编程方式读写 B 站内容的场景，必须触发本技能。 --- # bilibili-hub > **改造来源**：[jackwener/bilibili-cli](https://github.com/jackwener/bilibili-cli)（Apache-2.0） > > 本技能在原仓库基础上做了以下简化与改造： > - 移除 `browser-cookie3` / `click` / `rich` / `PyYAML` / `qrcode` 依赖 > - Cookie 认证改为直接传入 `dict` 或从环境变量读取，不做浏览器自动提取 > - 移除 CLI 层（commands/）、QR 登录、formatter 等 > - 保留全部 API 方法，统一封装为同步接口（`asyncio.run`） > - 核心依赖 `bilibili-api-python`（逆向工程 B 站 API 的第三方 SDK） > - 在 Minis 环境中，Cookie 通过 `browser_use get_cookies` 自动获取 --- ## 文件结构 ``` /var/minis/skills/bilibili-hub/ ├── SKILL.md ├── pyproject.toml # bilibili-api-python + aiohttp └── scripts/ ├── __init__.py ├── exceptions.py # 6 种结构化异常 ├── payloads.py # 数据结构规范化（normalize_* 函数） └── client.py # BiliClient 核心类（全部 API 方法） ``` --- ## 认证方式 B 站 Web API 使用三个关键 Cookie： | Cookie | 说明 | |--------|------| | `SESSDATA` | 用户 Session（必填，读操作） | | `bili_jct` | CSRF Token（写操作必填：点赞/投币/发动态等） | | `DedeUserID` | 用户 ID（建议填写） | | `buvid3` | 设备 ID（建议填写，降低风控概率） | ### 方法一：browser_use 自动获取（Minis 环境首选） 1. `browser_use navigate` 打开 `https://www.bilibili.com`，确认已登录 2. `browser_use get_cookies` 获取 Cookie（原始值不出现在对话中） 3. 加载 offload env 文件： ```bash . /var/minis/offloads/env_cookies_www_bilibili_com_xxx.sh export BILI_SESSDATA="$COOKIE_SESSDATA" export BILI_JCT="$COOKIE_BILI_JCT" export BILI_USERID="$COOKIE_DEDEUSERID" export BILI_BUVID3="$COOKIE_BUVID3" ``` > **注意**：`get_cookies` 仅对当前页面域名生效，需先 navigate 到 `https://www.bilibili.com` 再调用。 ### 方法二：手动从浏览器 DevTools 获取 1. 登录 B 站，打开 DevTools → Application → Cookies → `https://www.bilibili.com` 2. 找到 `SESSDATA`、`bili_jct`、`DedeUserID` 的值 3. 存入 Minis 环境变量：`BILI_SESSDATA` / `BILI_JCT` / `BILI_USERID` ### Cookie 传入方式（三种） ```python # 方式一：
Expert in Elixir, Phoenix Framework, and OTP. Specializes in building concurrent, fault-tolerant, and real-time applications using the BEAM. Use when building Elixir applications, working with Phoenix, implementing GenServers, or designing distributed systems on the BEAM.
Node.js / Python 接口自动化与签名还原工程技能：对自有平台或已授权平台的 Web API 进行签名分析与接口对接， 通过 Camoufox 反检测浏览器动态调试与静态源码分析，定位并还原前端加密/签名逻辑， 使用 Node.js 或 Python 实现算法复现与自动化接口调用。 深度集成 camoufox-reverse MCP v0.8.0（C++ 引擎级指纹伪装，78 个逆向分析工具，域级 Session 档案 + 断言系统）。 擅长 JSVMP 虚拟机保护的双路径攻克：路径 A 算法追踪（Hook / 插桩 / 日志分析 / 源码级插桩四板斧， 通用对RS 5/6、Akamai sensor_data、webmssdk、obfuscator.io）、 路径 B 环境伪装（jsdom/vm 沙箱 + 浏览器环境采集对比 + 全量补丁）。 v2.6.0 新增反爬类型三分法（签名型/行为型/纯混淆）作为顶层决策框架，明确 pre_inject_hooks 与 hook_jsvmp_interpreter(mode="proxy") 对签名型反爬不可用， 引入 mode="transparent" 签名安全备选与 MCP 侧 AST 源码插桩（消除 CDN 依赖）。 v2.9.0 新增域级 Session 档案（跨任务复用反爬判定/指纹基准/Cookie 归因）与断言驱动交付体系， Phase 5 升级为断言驱动结构化交付，新增降级梯度原则防止 AI 过早放弃。
微信自动化操作 skill，用于帮助用户快速完成微信消息群发、文件发送、群管理、聊天记录获取等自动化任务。当用户需要批量发送微信消息、管理微信群、获取聊天记录、或进行其他微信自动化操作时使用此 skill。
Use when a human wants to share a logged-in tab from the isolated OpenClaw browser so the agent can work through LobsterLink in that authenticated session. Triggers include requests to share a tab, give a LobsterLink peer/share ID, use a logged-in tab, or host/stop hosting a tab through LobsterLink. Skip install/reinstall if INSTALLED is already marked true in this skill.
Scaffolds the minimum repository structure required by session-orchestrator. Invoked automatically by the Bootstrap Gate when CLAUDE.md, Session Config, or bootstrap.lock is missing. Also available as /bootstrap for manual invocation.
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Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.
Query previous pi sessions to retrieve context, decisions, code changes, or other information. Use when you need to look up what happened in a parent session or any other session file.
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
├─ ⭐ 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
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.
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.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
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.
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.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused 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.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
