Loading...
Loading...
Found 13,481 Skills
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
Headless browser automation using Vercel's agent-browser CLI. 93% less context than Playwright MCP. Snapshot + refs workflow with element references. Use when automating browser tasks, web scraping, form filling, or content capture.
Extract project-specific coding rules and domain knowledge from existing codebase, generating markdown documentation for AI agents.
Configure which review agents run for your project. Auto-detects stack and writes compound-engineering.local.md.
Analyzes and optimizes an existing agent skill for conciseness, discoverability, and adherence to best practices. Use when a skill needs improvement, is too verbose, has poor activation rates, or fails to follow progressive disclosure patterns. Do NOT use for creating a new skill from scratch — use create-skill instead.
Set up and run the autonomous agent loop — auto-resolves prerequisites (MCP, wallet, registration), scaffolds files, enters perpetual cycle. Compatible with Claude Code and OpenClaw.
Use when entering orchestrator mode to manage agents via Paseo CLI
Overview The Amazon Agent is a high-performance tool designed to turn massive e-commerce datasets into structured, usable intelligence. It allows users to extract data from Amazon to monitor pricing,
Use this skill when the user's Copilot Studio agent evaluations have come back and they need to interpret scores, diagnose root causes of underperforming test cases, find remediation steps, or analyze patterns to improve their agent. Always use this skill when the user mentions: "eval failed", "why did this fail", "triage", "diagnose failure", "low pass rate", "fix evaluation results", "not passing", "failing test cases", "evaluation results", "improve my eval scores", or any situation where eval scores need interpretation and action.
Use this skill when the user wants to spend money, make purchases, send crypto, pay for APIs, browse websites for shopping, complete checkout, or manage an AI agent's payment wallet. Covers buying products online with credit cards (including browser-automated checkout), sending tokens, paying for x402 protocol APIs, checking balances, depositing funds, browsing available services, and signing on-chain transactions — all with secure guardrails, and appropriate human controls. Trigger on any spending, wallet, or shopping intent: "buy this", "pay for that", "send tokens", "how much do I have", "what can I buy", "top up my wallet", "get a card", "set up payments", "find me something to buy", "complete the checkout", or "browse that site" — even if the user doesn't mention "lobster", "crypto", or "Solana" directly.
End-to-end implementation orchestrator. Use when the user says "orchestrate", "implement this end to end", "build this", or wants a full feature/fix implemented through a team of agents with planning, implementation, review, and QA phases.
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.