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Found 5,676 Skills
Use the xurl CLI to resolve unified agents:// URIs (and legacy provider URIs) for Amp, Codex, Claude, Gemini, Pi, and OpenCode thread reading workflows.
Bitcoin L1 wallet for agents - check balances, send BTC, manage UTXOs. Extends to Stacks L2 (STX, DeFi) and Pillar smart wallets (sBTC yield).
Browser automation CLI for AI agents - create, test, and deploy web automations
Create event-driven hooks for AI coding agent automation (Claude Code, Codex CLI). Configure hook events in settings or frontmatter, parse stdin JSON inputs, return decision-control JSON, and implement secure hook scripts.
Generate production-ready REVIEW.md and AGENTS.md files for Devin Review's AI code review system. Use this skill whenever the user mentions Devin Review, REVIEW.md, Devin code review setup, PR review instructions for Devin, AI code review configuration for Devin, or wants to create instruction files that Devin's Bug Catcher uses. Also trigger when someone says "set up Devin review", "configure Devin for our repo", "create review rules for Devin", or asks about REVIEW.md / AGENTS.md — even if they don't say "Devin" explicitly but describe wanting AI-powered PR review instructions that work with Devin's auto-review or Bug Catcher.
Generate personalized illustrated storybooks with custom artwork. Supports 5-10 pages (default 6), age-appropriate text length (3-18 years), and multiple art styles (watercolor, cartoon, pixel-art, claymation, comic, coloring-book). Use when creating picture books, children's storybooks, illustrated stories, or any request involving generating a story with images for children.
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
Manage Function Compute AgentRun resources via OpenAPI (runtime, sandbox, model, memory, credentials). Use for creating runtimes/endpoints, querying status, and troubleshooting AgentRun workflows.
Design and scaffold the code execution pattern for MCP-based agent systems. Use when building agents that interact with many MCP tools, when intermediate data is too large for model context, when you need loops/conditionals across tool calls, or when PII must stay out of the model context. Based on Anthropic's engineering guidance.
Reviews chapter quality with checker agents and generates reports. Use when the user asks for a chapter review or runs /webnovel-review.
Copilot agent that assists with bug investigation, root cause analysis, and fix generation for efficient debugging and issue resolution Trigger terms: bug fix, debug, troubleshoot, root cause analysis, error investigation, fix bug, resolve issue, error analysis, stack trace Use when: User requests involve bug hunter tasks.
This skill guides the agent in identifying and replacing AI model-specific cliches and formulaic expressions with more natural, human-like language, grounded in external search for better alternatives.