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Import Skills

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fakechris fakechris
from GitHub Data & AI
  • 📄 SKILL.md
vault pipeline ovp

obsidian-vault-pipeline

使用 Obsidian Vault Pipeline 自动化整理知识库。 **触发场景：** - 用户说 "运行 WIGS 流程"、"整理 Obsidian Vault"、"处理知识库" - 用户说 "提取 Evergreen"、"更新 MOC"、"运行 Pipeline" - 用户提到 "整理笔记"、"知识管理"、"处理书签" - 用户说 "质检"、"质量检查"、"检查一致性" **Vault 位置设置：** 默认使用当前工作目录作为 vault 根目录，或通过 `--vault-dir` 参数指定。 只要用户提到 Obsidian、知识管理、WIGS、Pipeline、Evergreen、MOC 等关键词，就立即使用此 skill。 --- # Obsidian Vault Pipeline Skill ## 概述 此 skill 用于帮助用户运行 Obsidian Vault Pipeline 自动化知识管理流程。 ## 安装 ```bash pip install obsidian-vault-pipeline ``` ## Vault 位置设置 Pipeline 自动检测 vault 位置（按优先级）： 1. **当前工作目录** - 默认使用 `cwd` 2. ** `--vault-dir` 参数** - 显式指定 3. **环境变量** - `VAULT_DIR` **最佳实践：** ```bash cd /path/to/my-vault # 进入 vault 目录 ovp --check # 检查环境 ovp --full # 运行完整 pipeline ``` ## 可用命令 | 命令 | 说明 | |------|------| | `ovp --check` | 检查环境配置 | | `ovp --init` | 初始化配置（交互式） | | `ovp --full` | 运行完整 pipeline | | `ovp-article --process-inbox` | 处理 50-Inbox/01-Raw/ 中的文章 | | `ovp-evergreen --recent 7` | 提取最近7天的 Evergreen 笔记 | | `ovp-moc --scan` | 扫描并更新 MOC 索引 | | `ovp-quality --recent 7` | 质量检查 | ## 标准操作流程 ### 1. 首次使用 ```bash # 进入 vault 目录 cd my-vault # 检查环境 ovp --check # 如果提示未配置，运行初始化 ovp --init ``` ### 2. 日常处理 ```bash # 放入新文章到 50-Inbox/01-Raw/ cp article.md my-vault/50-Inbox/01-Raw/ # 运行 pipeline ovp --full ``` ### 3. WIGS 完整性检查 ```bash # 5层一致性检查 ./60-Logs/scripts/check-consistency.sh # 自动修复低风险问题 ./60-Logs/scripts/repair.sh --auto ``` ## 配置文件 在 vault 根目录创建 `.env`： ```bash AUTO_VAULT_API_KEY=your_api_key AUTO_VAULT_API_BASE=https://api.minimaxi.com/anthropic AUTO_VAULT_MODEL=minimax/MiniMax-M2.5 ``` ## 触发词映射 | 用户说 | 执行命令 | |--------|----------| | "运行 WIGS 流程" | `./60-Logs/scripts/check-consistency.sh` | | "整理 Obsidian" | `ovp --full` | | "处理文章" | `ovp-article --process-inbox` | | "提取 Evergreen" | `ovp-evergreen --recent 7` | | "更新 MOC" | `ovp-moc --scan` | | "质量检查" | `ovp-quality --recent 7` | | "检查一致性" | `./60-Logs/scripts/check-consistency.sh` | ## 处理流程 ``` 50-Inbox/01-Raw/ → ovp-article → 20-Areas/深度解读 20-Areas/ →

⬇0 ❤87 28 days ago · Uploaded Detail →
BANANASJIM BANANASJIM
from GitHub Data & AI
  • 📁 references/
  • 📄 __init__.py
  • 📄 SKILL.md
gpu assertions inspecting

rdc-cli

Use this skill when working with RenderDoc capture files (.rdc), analyzing GPU frames, tracing shaders, inspecting draw calls, or running CI assertions against GPU captures.

⬇0 ❤88 1 month ago · Uploaded Detail →
CodeAlive-AI CodeAlive-AI
from GitHub Development & Coding
  • 📁 references/
  • 📁 scripts/
  • 📄 .gitignore
  • 📄 README.md
  • 📄 setup.py
search patterns semantic

codealive-context-engine

Semantic code search and AI-powered codebase Q&A across indexed repositories. Use when understanding code beyond local files, exploring dependencies, discovering cross-project patterns, planning features, debugging, or onboarding. Queries like "How does X work?", "Show me Y patterns", "How is library Z used?". The default path is semantic search plus grep search; chat-with-codebase is slower, more expensive, and usually secondary.

⬇0 ❤78 16 days ago · Uploaded Detail →
swt-labs swt-labs
from GitHub Development & Coding
  • 📄 SKILL.md
claude smoke ai

running-claude-smoke-tests

This skill should be used when the user asks to run or verify a VBW smoke test with plain Claude Code (`claude`), capture visible `Skills:` output, validate `.vbw-planning/.skill-decisions.log`, or confirm consumer-smoke-worktree versus `--plugin-dir` provenance for local smoke coverage in this repo.

⬇0 ❤68 9 days ago · Uploaded Detail →
CleverCloud CleverCloud
from GitHub Ops & Delivery
  • 📁 references/
  • 📄 SKILL.md
clever deploy devops

clever-tools

CLI to deploy and manage applications, add-ons, and configurations on Clever Cloud PaaS. Use when the user needs to deploy apps, view logs, manage environment variables, configure domains, or interact with Clever Cloud services.

⬇0 ❤86 1 month ago · Uploaded Detail →
JessyTsui JessyTsui
from GitHub Tools & Productivity
  • 📄 SKILL.md
automation cerul search

cerul-api

Use Cerul's video search API from Codex or Claude-style agents. Trigger when a user wants to search videos with Cerul, inspect Cerul usage, or integrate Cerul search into scripts or agent workflows. Requires CERUL_API_KEY and optionally CERUL_BASE_URL.

⬇0 ❤87 1 month ago · Uploaded Detail →
archibate archibate
from GitHub Tools & Productivity
  • 📄 SKILL.md
user agent send

cc-connect

This skill should be used when sending images, files, or notifications back to the user via messaging platforms (Discord, Feishu, Telegram, etc.) through cc-connect. TRIGGER when agent generates a plot/chart/screenshot and wants to show the user; agent creates a report/PDF/file the user should receive; agent needs to proactively notify the user (e.g. task completed, alert, reminder); user asks to "send image", "show me the chart", "notify me", "send the file", "send to Telegram", "show plot in Discord".

⬇0 ❤86 1 month ago · Uploaded Detail →
iswalle iswalle
from GitHub Docs & Knowledge
  • 📁 references/
  • 📁 scripts/
  • 📄 .gitignore
  • 📄 LICENSE
  • 📄 package.json
笔记 get 保存

Get笔记

Get笔记 - 保存、搜索、管理个人笔记和知识库。 **当以下情况时使用此 Skill**： (1) 用户要保存内容到笔记：发链接、发图片、说「记一下」「存到笔记」「保存」「收藏」 (2) 用户要搜索或查看笔记：「搜一下」「找找笔记」「最近存了什么」「看看原文」 (3) 用户要管理知识库或标签：「加到知识库」「建知识库」「加标签」「删标签」 (4) 用户要配置 Get笔记：「配置笔记」「连接 Get笔记」

⬇0 ❤85 29 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