Total 50,652 skills, AI & Machine Learning has 8491 skills
Showing 12 of 8491 skills
Skill to create custom agents for VS Code Copilot or OpenCode, helping users configure and generate agent files with proper formatting and configurations. Use when users want to create specialized AI assistants for VS Code Copilot (.agent.md files) or OpenCode (JSON/markdown agent configs) with specific tools, prompts, models, and behaviors. If the user is not specific about the target platform, ask them to specify Copilot or OpenCode.
Meta-prompting framework for critiquing responses, analyzing solution trajectories, and evaluating AI-generated content quality
Autonomous development agent that picks tasks from a project board (Jira, ClickUp, GitHub Issues), explores the codebase, implements the solution, opens a PR, and notifies the team. Configurable per-project via project files in ~/.config/delivering-tickets/projects/. Use this skill when the user asks to "work on a ticket", "pick up a task", "implement issue X", "work autonomously on the board", "take the next task", or any variation of autonomous task execution from a project board. Also triggers when the user mentions delivering-tickets, project configuration, or wants to set up autonomous development workflows for their team. Available commands: /delivering-tickets (start), /delivering-tickets:check (check replies), /delivering-tickets:status (workflow status), /delivering-tickets:setup (verify environment), /delivering-tickets:project (manage projects). Do NOT use for general coding without a ticket, standalone code reviews, project setup without a board configured, or questions unrelated to task execution from a project board.
A 10-step methodology for building software with AI collaboration - from north star through automated Ralph loop execution with zero human-in-the-loop code writing
Use this skill when you need guidance on which skill to use for any task. Recommends the perfect skill, creates skill combinations, and helps you discover capabilities you didn't know you had.
Provides strategic insights on AI-driven software democratization and agent-based development trends from Replit's perspective. Use when discussing the future of software engineering, AI agent infrastructure requirements, democratization of coding, or when analyzing how AI will transform software creation from expert-only to universal access. Triggers include questions about software engineering automation trends, agent sandbox environments, SWE-bench benchmarks, or strategic implications of AI coding assistants for startups and enterprises.
Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents). Use when the user wants to register their agent identity on-chain, create an agent profile, claim an agent NFT, set up agent reputation, or make their agent discoverable. Handles bridging ETH to mainnet, IPFS upload, and on-chain registration.
This skill is used when the user requests 'review my prompt', 'analyze my conversation history', 'diagnose my understanding level', or when it is invoked via /prompt-review. It reads past AI Agent conversation histories (Claude Code, GitHub Copilot Chat, Cline, Roo Code, Windsurf, Antigravity), estimates the user's technical understanding level, prompting patterns and AI dependency, then generates a corresponding report.
This skill adds data(like resources) to OpenViking Context Database (aka. ov). Use when an agent needs to add files, data from URLs, or external knowledge during interactions. Trigger this tool when 1. is explicitly requested adding files or knowledge; 2. identifies valuable resources worth importing; 3. the user mentioned adding to OV/OpenViking/Context Database. This skill helps how to use CLI like `ov add-resource`, `ov add-skill` and `ov add-memory` to add resource data, skill files, memory files to OpenViking.
A guided, zero-friction installer and maintenance assistant for OpenClaw. Use this skill when the user wants to install OpenClaw, set up OpenClaw on a local machine or remote server, connect OpenClaw to DingTalk, get OpenClaw skill recommendations for their use case, or perform post-installation maintenance (health checks, troubleshooting, installing new skills, changing AI models, adding chat channels, updating OpenClaw). Handles full environment detection, installation, optional DingTalk integration, scene-based skill recommendations, and daily maintenance — all interactively, with no wasted steps.
Complete guide for building MCP servers with FastMCP 3.0 - tools, resources, authentication, providers, middleware, and deployment. Use when creating Python MCP servers or integrating AI models with external tools and data.
Use when the user wants tool use, MCP access, HTTP or streaming API exposure, auto-function helpers, or wait-for-key behavior through Agently-native extension surfaces rather than custom wrappers first.