Loading...
Loading...
Found 416 Skills
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.
End-to-end orchestration for non-trivial software feature development. Use this skill whenever the user asks to implement a PR-sized feature, break down a plan, have subagents review a plan, run a plan-review-development-acceptance loop, coordinate multiple review perspectives, produce an acceptance report, or generate an HTML PR summary. Prefer this skill for multi-step code changes even if the user only says "build this feature" and the task is not a tiny one-file edit.
This skill is used when users provide one or more slide images, image-based PPT/PPTX or PDF files, and request conversion to editable PowerPoint/PPTX, reconstruction of slide objects, retention of page notes, or editable replication.
Use when tasks are complex and require full microservices collaboration: The main agent acts as a pure Orchestrator, strictly prohibited from writing code personally, and is responsible for accurately assigning responsibilities such as positioning, planning, coding, testing, and review to corresponding sub-agents (explorer, planner, worker, verifier, reviewer, fixer). This Skill enforces microservices workflow discipline, requiring full Chinese communication, minimal routing output, and minimized context transfer.
Adversarial due-diligence on a benchmark you envy — a founder, KOL, company, or product whose claimed success you suspect is inflated. Inline four-phase orchestration — fan-out collection, adversarial verification grading every claim L1-L4 to split marketing bubble from real signal, attribution weighting (product vs timing vs IP vs luck, what's replicable), then mapping the validated playbook onto the user's own resources. Use whenever the user wants to 尽调/对标/拆解 a competitor or role-model, 抄/偷师 someone's playbook, suspects 水分/泡沫 in their claims (Product Hunt
Expert cuTile programming assistant. Write high-performance GPU kernels using cuTile's tile-based programming model with proper validation and optimization. Supports deep agent orchestration for complex multi-kernel tasks.
Research how to implement a phase standalone, investigating implementation approaches before planning, or re-researching after planning is complete. Triggers include "research phase", "investigate phase", "how to implement", "research implementation", and "phase research".
Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.
OpenProse is a programming language for AI sessions. Activate on ANY `prose` command (prose boot, prose run, prose compile, prose update, etc.), running .prose files, mentioning OpenProse/Prose, or orchestrating multi-agent workflows. The skill intelligently interprets what the user wants.
Agent skill for migration-plan - invoke with $agent-migration-plan
Build production-ready AI agents using Google's Agent Development Kit with AI assistant integration, React patterns, multi-agent orchestration, and comprehensive tool libraries. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Orchestrate multiple independent agents running simultaneously, leveraging Claude Sonnet 4.5's parallel tool execution capabilities to maximize throughput on multi-task requests.