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Found 110 Skills
Manages parent/child agent relationships with task delegation and result aggregation. Supports sequential chains, parallel fans, conditional routing, retry logic, timeout handling, and YAML-based visual workflow definition.
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Multi-agent coordination expert for agent-swarm MCP. Use when the user asks about swarm coordination, delegating tasks to agents, checking swarm status, agent messaging, or managing multi-agent workflows.
Agent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents, evaluating CrewAI/AutoGen/Swarm, or orchestrating complex multi-step scenarios.
Coordinate AI agent teams via a Kanban task board with local JSON storage. Enables multi-agent workflows with a Team Lead assigning work and Worker Agents executing tasks via heartbeat polling. Perfect for building AI agent command centers.
Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
Task-based multi-agent coordination (includes Issue Remediation Loop)
Use when an approved current phase has 3 or more independent ready tasks and parallel execution will materially reduce cycle time. Orchestrates bounded workers, monitors blockers and file conflicts, coordinates rescues, and hands off to planning or reviewing when the current execution scope is complete. Use for prompts about swarming, parallel workers, launching multiple agents, coordinating a worker pool, or running approved current-phase work at scale.
N coordinated agents on shared task list using tmux-based orchestration
AI Agent Harness Design Patterns - Memory, Permission, Context Engineering, Delegation, Skill, Hook, Bootstrap. Chinese Version.
Plan how to slice a non-trivial coding task across parallel subagents. Returns a dispatch plan (file assignments, dependencies, output-format contracts) — the main Agent then executes it with the Agent tool + `isolation: "worktree"`. Invoke only when work justifies multi-agent overhead: (a) greenfield 0→1 across multiple independent modules, (b) change touches ≥3 modules, or (c) ≥5 files each with >50 lines of diff. Small changes write inline.
Autonomous pipeline manager that orchestrates the entire development workflow. You are the leader of this process.