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Found 1,182 Skills
Example project-specific skill template based on a real production application.
Publish files and folders to the web instantly. Use when asked to "publish this", "host this", "deploy this", "share this on the web", "make a website", or "put this online". Outputs a live URL at <slug>.here.now.
Preflight Google Play releases, validate edits, and verify listing completeness with gpd. Use when shipping to production or troubleshooting a failed release.
Expert knowledge for setting up, configuring, and extending Grimmory — a self-hosted book library manager supporting EPUBs, PDFs, comics, Kobo sync, OPDS, and multi-user management.
Deploy and run ML experiments on local or remote GPU servers. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.
Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.
Guide to deploying and managing OpenClaw-compatible AI agent systems across cloud, bare metal, and hybrid infrastructure.
Skill for using Astro projects. Includes CLI commands, project structure, core config options, and adapters. Use this skill when the user needs to work with Astro or when the user mentions Astro.
This skill should be used when the user wants to list all projects, switch projects, rename a project, enable/disable PR deploys, make a project public/private, or modify project settings.
This skill should be used when the user says "setup", "deploy to railway", "initialize", "create project", "create service", or wants to deploy from GitHub. Handles initial setup AND adding services to existing projects. For databases, use the database skill instead.
This skill should be used when the user wants to add a service from a template, find templates for a specific use case, or deploy tools like Ghost, Strapi, n8n, Minio, Uptime Kuma, etc. For databases (Postgres, Redis, MySQL, MongoDB), prefer the database skill.
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.