- 📄 SKILL.md
app-launcher-skill
Launch Android applications by package name. Open any installed app programmatically.
Launch Android applications by package name. Open any installed app programmatically.
Multi-Platform Content Discovery for AI Agents
Automatically analyze a codebase and generate an architecture diagram with zero configuration. Use when the user asks to "diagram this repo", "visualize the architecture", "auto diagram", or requests a codebase overview without specifying components. Do NOT use when the user provides a specific description, sample diagram, or component list — use the excalidraw skill instead.
ClawMem agent reference — detailed operational guidance for the on-device hybrid memory system. Use when: setting up collections/indexing/embedding, troubleshooting retrieval, tuning query optimization (4 levers), understanding pipeline behavior, managing memory lifecycle (pin/snooze/forget), building graphs, or any ClawMem operation beyond basic tool routing.
Use this when you need to scrape websites, extract page content, download media, or run the ArchiveBox extractors without a full ArchiveBox install. abx-dl can save many kinds of web content including txt, md, html, json, pdf, png, jpg, mp4, mp3, srt, screenshots, favicons, headers, DOM snapshots, mirrored sites, and more using the same plugin ecosystem that powers ArchiveBox.
The master coordinator for AI skills. Discovers skills from multiple sources (SkillsMP.com, SkillHub, and ClawHub), manages installation, and synchronization across Claude Code, Gemini CLI, Google Anti-Gravity, OpenCode, and other AI tools. Handles User-level (Global) and Project-level (Local) scopes.
AI pair programming with real-time screen and audio context. Use when the user wants to record their screen, start/stop recording, or get context from what they're doing.
Install or enable Secure Claude Code with the recommended balanced baseline.
Author, debug, and operate Kelos resources (Task, Workspace, AgentConfig, TaskSpawner) on Kubernetes. Use when working with Kelos CRDs or the kelos CLI.
Use when running demo recordings, diagnosing recording failures, or regenerating GIFs from existing MP4s. Covers the Docker + VHS + ffmpeg pipeline. --- # VHS Demo Recording Use this skill to run, debug, or regenerate gh-infra demo GIF recordings. ## When To Use - Running `make demo` or `docs/tapes/vhs.sh` directly - Diagnosing why a recording failed or produced a 0-byte GIF - Regenerating GIFs from existing MP4s without re-recording - Understanding the recording pipeline ## Prerequisites - Docker must be running - Go toolchain (for cross-compiling the Linux binary) ## Pipeline ```text make demo 1. go build -o docs/tapes/.gh-infra (GOOS=linux GOARCH=amd64) 2. docs/tapes/vhs.sh a. docker build → gh-infra-vhs image (VHS + vim) b. For each *.tape in parallel: docker run --memory=1g --cpus=2 → produces .mp4 c. For each .mp4 sequentially: docker run jrottenberg/ffmpeg:7-alpine → produces .gif 3. Copy GIFs to docs/public/ 4. Clean up .gh-infra binary ``` ## Why MP4 → GIF Instead of Direct GIF VHS's built-in GIF output is unreliable when multiple containers run in parallel on macOS. The workaround is to output MP4 only from VHS, then convert to GIF via ffmpeg with high-quality settings (lanczos scaling, sierra2_4a dithering, 256 colors). ## Key Files | File | Role | |------|------| | `docs/tapes/vhs.sh` | Orchestrator: parallel recording + sequential GIF conversion | | `docs/tapes/Dockerfile` | `ghcr.io/charmbracelet/vhs` + vim | | `docs/tapes/*.tape` | VHS scenario files | | `docs/tapes/setup*.sh` | Per-demo setup scripts (mock data, gh wrapper) | | `docs/tapes/mock-gh` | Generic mock for `gh` CLI | | `docs/tapes/.gh-infra` | Cross-compiled Linux binary (ephemeral) | ## Output Locations - Raw recordings: `docs/tapes/*.mp4` and `docs/tapes/*.gif` - Published assets: `docs/public/demo*.gif` (copied by Makefile) ## Environment Variables `make demo` forwards `DEMO_ENV` variables into Docker via `-e` flags. Use this to pass environment overrides (e.g. `GH_INFRA_OUTPUT`) into
Write effective Architecture Decision Records. Use when: (1) Creating a new ADR, (2) Recording a design decision, (3) User mentions ADR, decision, trade-off, or alternatives
Investigate data incidents and find root causes using Monte Carlo's observability data. Guides the agent through systematic investigation: alert lookup, lineage tracing, ETL checks, query analysis, and data profiling. Activates when a user asks about data issues, incidents, alerts, or why data looks wrong.
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: