🕸️ Agent Orchestration AI Skills

Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks

#1 on DeepResearch Bench (Feb 2026). Any-to-Any AI for agents. Combines deep reasoning with all modalities through sophisticated multi-agent orchestration. R...

Complete toolkit for creating autonomous AI agents and managing Discord channels for OpenClaw. Use when setting up multi-agent systems, creating new agents, or managing Discord channel organization.

Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.

Deterministically coordinates autonomous planning and execution across available skills under strict guardrails. Use only when the user explicitly activates this skill by name to run autonomously until a stop command is issued. Trigger keywords include: "use autonomous-skill-orchestrator", "activate autonomous-skill-orchestrator", "start autonomous orchestration".

Multi-agent workflow orchestration for OpenClaw. Use when user mentions antfarm, asks to run a multi-step workflow (feature dev, bug fix, security audit), or...

Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.

Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.

Use when executing implementation plans with independent tasks in the current session

Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.

协调并管理多个AI子Agent（Learner、Critic等）进行任务分工、通信和结果整合，实现复杂任务的多Agent协作。

Delegate complex coding, research, or autonomous tasks to Agent Zero framework. Use when user says "ask Agent Zero", "delegate to A0", "have Agent Zero build", or needs long-running autonomous coding with self-correction loops. Supports bidirectional communication, file attachments, task breakdown, and progress reporting.

PIV workflow orchestrator - Plan, Implement, Validate loop for systematic multi-phase software development. Use when building features phase-by-phase with PRPs, automated validation loops, or multi-agent orchestration. Supports PRD creation, PRP generation, codebase analysis, and iterative execution with validation.

Multi-agent war room for brainstorming, system design, architecture review, product specs, business strategy, or any complex problem. Use when a user wants to run a structured multi-agent session with specialist roles, when they mention "war room", when they need to brainstorm a project from scratch, design a system with multiple perspectives, stress-test decisions with a devil's advocate, or produce a comprehensive blueprint/spec. Works for software, hardware, content, business — any domain.

Constrained autonomous delegate for identity-proxied communication. Handles incoming messages (Email, Discord, Slack, WhatsApp) by analyzing intent and applying declarative authority policies before generating responses. Use when the user wants to delegate communication tasks while maintaining identity fidelity and enforcing strict non-overreach boundaries.

Python orchestration skill: local multi-agent workflows via blackboard file, permission gating, and token budget scripts. All execution is local — no network...

Multi-agent debate council — spawns 3 specialized sub-agents in parallel (Scholar, Engineer, Muse) for Round 1, then optional Round 2 cross-examination to ch...

IMPORTANT: OpenRouter is required. Routes tasks to the right model and always delegates work through sessions_spawn.

Chain skills into automated pipelines with conditional logic, error handling, and audit logging. Define workflows in YAML or JSON, then execute them hands-fr...

Avoid common TensorFlow mistakes — tf.function retracing, GPU memory, data pipeline bottlenecks, and gradient traps.

A persistent local-only memory system for AI coding agents. Two files, one idea — AGENTS.md (committed, shared) + .agents.local.md (gitignored, personal). Agents read both at session start, update the scratchpad at session end, and promote stable patterns over time. Works across Claude Code, Cursor, Copilot, Windsurf. Subagent-ready. No plugins, no infrastructure, no background processes.

Persistent task ledger for agent coordination. Plan multi-step work, checkpoint progress across session boundaries, and coordinate across multiple agents wit...

OpenProse VM skill pack. Activate on any `prose` command, .prose files, or OpenProse mentions; orchestrates multi-agent workflows.

This skill enables one-click generation of multiple AI agents based on a user prompt, outputs their organizational structure, and visualizes their collaborat...