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Found 2,319 Skills
Self-evolving AI agent system with 26 tools, three-layer memory, MCP plugins, and 24/7 self-repair in pure Python.
Decide how to implement runtime and API changes in openai-agents-js before editing code. Use when a task changes exported APIs, runtime behavior, schemas, tests, or docs and you need to choose the compatibility boundary, whether shims or migrations are warranted, and when unreleased interfaces can be rewritten directly.
PokeClaw (PocketClaw) — on-device Android AI phone agent using Gemma 4 via LiteRT-LM with tool calling, accessibility automation, and optional cloud models.
Implement feature tasks using AI agents in logical batches, track completion status, identify blockers, and manage task handoffs. Use when you have an execution sequence and need AI agents to build tasks while maintaining progress tracking.
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.
Claude Code subagents for offensive security research, penetration testing planning, recon analysis, exploit research, detection engineering, and security reporting
Marketing skills collection for AI agents - CRO, copywriting, SEO, analytics, and growth engineering
Better proposals, faster closes. Use when creating AI agent pricing, automation proposals, ROI calculations, or sales materials. Generates professional pricing pages, case studies, and closing scripts for AI automation services.
A minimal teaching framework for understanding AI Agent architecture with core loop, fake LLM interface, and skill discovery system
Build and operate multi-agent workflows with OpenAI Agents SDK (Python): define agents/tools/handoffs, add guardrails, run conversations, and debug orchestration behavior. Use when users ask for agent orchestration with OpenAI-native patterns, handoff routing, or production-ready agent loops.
Configure Celigo AI agent and guardrail imports -- LLM-powered steps that classify, extract, validate, or generate data within flows. Use when creating agent imports (OpenAI, Gemini), guardrails (PII, moderation), or configuring prompts, structured output, or BYOK connections.
Use when creating cloud sandboxes (microVMs) to run code, start dev servers, and generate live preview URLs. Also covers deploying AI agents, MCP servers, batch jobs, and Agent Drives (shared filesystems) on Blaxel's serverless infrastructure. Reach for this skill when you need isolated compute environments, real-time app previews, shared file storage across sandboxes, or to deploy agentic workloads.