Redc-useage
Multi-cloud red team infrastructure automation. Deploy and manage cloud resources across AWS, Aliyun, Tencent Cloud with Terraform. Includes commands for init, deploy, manage, execute, and cleanup of infrastructure cases.
Free to get · One-click to use
Multi-cloud red team infrastructure automation. Deploy and manage cloud resources across AWS, Aliyun, Tencent Cloud with Terraform. Includes commands for init, deploy, manage, execute, and cleanup of infrastructure cases.
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.
Multi-AI gateway for fullstack apps. Build/deploy websites, React apps, SaaS, ecommerce to Cloudflare Workers. DB (D1/KV/R2), Stripe payments/subscriptions/checkout, auth (login, OAuth, OTP), AI image/audio/video/TTS generation, email, presentations/slides, web scraping/search, CEO interviews/quotes, document parsing/extraction, SMS verification, serverless deploy/API/webhook.
Create and deploy reusable React components for Webflow Designer. Configure existing React projects with webflow.json, build and bundle code, validate output, and deploy to workspace using library share. Use when building custom components for designers.
This skill should be used when the user asks to "generate a setup script", "create a deploy script", "write a deployment script", "deploy to EC2", "deploy to production", "setup production server", "write setup.sh", "create deploy.sh", or discusses deploying a project to a remote server. Ensures deployment scripts include proper environment checks and safeguards.
Deploy the everyrow MCP server to staging or production on GKE. Use when the user wants to deploy, redeploy, roll back, scale replicas, or check deployment status. Triggers on deploy, redeploy, staging, production, rollout, scale, replicas.
Use when deploying a local project or codebase to Zeabur. Use when the user says "deploy this" or "deploy to Zeabur". Default to direct deploy unless the user explicitly asks for Git-based deployment.
Run, test, benchmark, upgrade, and deploy the Tycho simulation server in this repo (tycho-simulation-server). Use when starting/stopping the service, waiting for /status readiness, validating /simulate across many token pairs/pools/protocols (including VM pools like curve/balancer/maverick), computing p50/p90/p99 latencies, running load/stress tests, or verifying upgrades and deployments (cargo fmt/clippy/nextest/build, docker build, CDK synth/diff/deploy).
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: