Display ARP cache table with MAC vendor lookup and suspicious entry detection. Supports CSV, TSV, and TUI output. **Dependency**: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.
Create complete documentation sites for projects. Use when asked to: "create docs", "add documentation", "setup docs site", "generate docs", "document my project", "write docs", "initialize documentation", "add a docs folder", "create a docs website". Generates Docus-based sites with search, dark mode, MCP server, and llms.txt integration. --- # Create Docs Generate a complete, production-ready documentation site for any project. ## Workflow 1. **Analyze** - Detect package manager, monorepo structure, read context 2. **Initialize** - Create docs directory with correct setup 3. **Generate** - Write documentation pages using templates 4. **Configure** - Set up AI integration (MCP, llms.txt) 5. **Finalize** - Provide next steps with correct commands --- ## Package Manager Reference Detect from lock files, default to npm if none found: | Lock File | PM | Install | Run | Add | |-----------|------|---------|-----|-----| | `pnpm-lock.yaml` | pnpm | `pnpm install` | `pnpm run` | `pnpm add` | | `package-lock.json` | npm | `npm install` | `npm run` | `npm install` | | `yarn.lock` | yarn | `yarn install` | `yarn` | `yarn add` | | `bun.lockb` | bun | `bun install` | `bun run` | `bun add` | Use `[pm]` as placeholder in commands below. --- ## Step 1: Analyze Project ### Detect Project Structure ```
Install, configure, and start FireRed-OpenStoryline from source on a local machine. Use when a user asks to set up OpenStoryline, troubleshoot installation, download required resources, fill config.toml API keys, or launch the MCP and web services, as well as Chinese requests like “安装 OpenStoryline”, “配置 OpenStoryline”, “启动 OpenStoryline”, “把 OpenStoryline 跑起来”, “修复 OpenStoryline 安装问题”, or “排查 OpenStoryline 启动失败”.
Use when setting up a project environment — installing dependencies, verifying builds, detecting the tech stack. Covers Phase 0 of a new session.
Install and configure TMA1 local observability. Use when the user says: install tma1, setup observability, monitor my agent, track token usage, set up telemetry.
Create install.md files optimized for AI agent execution. Use for ANY question about install.md files or request to create/review installation documentation for autonomous agent use.
One-stop search and install for coding resources. Aggregates MCP Servers, Skills, Rules, and Prompts. Supports search, category browsing, project-based recommendations, and one-click install.
Lightweight guide and router for Markster OS. Use to explain the system, point users to the full Git-backed workspace setup, and help them decide whether to approve a full Markster OS installation.
Use when setting up a fresh HAINDY installation, configuring API credentials for the first time, migrating from a legacy .env file, or verifying the effective configuration.
Use when tasks involve browser automation with bridgic-browser via terminal CLI (`bridgic-browser ...`) or Python SDK (`from bridgic.browser.session import Browser`, `from bridgic.browser.tools import BrowserToolSetBuilder`). Trigger for navigation, scraping, form filling, accessibility snapshot refs, e2e checks, stealth browsing, CLI-SDK mapping/migration, and generating SDK code from CLI action steps. --- ## Prerequisite (Important!!) Before performing any operations, **MAKE SURE to use `uv`** to initialize the execution environment and install dependencies first. Note: DO NOT rely on any execution environment other than `uv`, to ensure the execution environment is isolated from the host machine. - **Initialize project**: `[ -f pyproject.toml ] || uv init --bare --python 3.10` - **Install dependencies**: `uv add --upgrade bridgic-browser`. - **Ensure that `uv` is available**: If `uv` is not found or not installed, run `pip install uv` to install it. Then rerun the previous "Install dependencies" step. - **Install browser binaries** (one-time): `uv run playwright install chromium` The CLI tools (`references/cli-guide.md`) and the Python SDK (`references/sdk-guide.md`) come from the **same package** — installing one installs both. ## Strategies & Guidelines (Important!!) When writing browser automation or web scraping code, **ALWAYS follow this "explore first, then coding" strategy**: - First, use the `bridgic-browser` CLI tools to explore the page structure. It is recommended to use headed mode with the command `bridgic-browser open --headed <url>` during exploration. - Then, use the `bridgic-browser` Python SDK to write the code.
jup is a command-line tool for installing and managing agent skills across different ai agents, scopes, and projects.
> Orchestrates skill discovery, installation, and project lifecycle.
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:
