orchestration AI Agent Skills

skypilot-multi-cloud-orchestration

21.8k

davila7

Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.

crewai-multi-agent

21.8k

davila7

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

sparc-methodology

17.8k

ruvnet

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

GitHub Release Management

17.8k

ruvnet

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

trulens-evaluation-workflow

3.1k

truera

Systematically evaluate your LLM application with TruLens

adk-agent-builder

1.5k

jeremylongshore

Build production-ready AI agents using Google's Agent Development Kit with Claude integration, React patterns, multi-agent orchestration, and comprehensive tool libraries

batching-patterns

241

MadAppGang

Batch all related operations into single messages for maximum parallelism and performance. Use when launching multiple agents, reading multiple files, running parallel searches, optimizing workflow speed, or avoiding sequential execution bottlenecks. Trigger keywords - "batching", "parallel", "single message", "golden rule", "concurrent", "performance", "sequential bottleneck", "speed optimization".

quality-gates

241

MadAppGang

Implement quality gates, user approval, iteration loops, and test-driven development. Use when validating with users, implementing feedback loops, classifying issue severity, running test-driven loops, or building multi-iteration workflows. Trigger keywords - "approval", "user validation", "iteration", "feedback loop", "severity", "test-driven", "TDD", "quality gate", "consensus".

error-recovery

241

MadAppGang

Handle errors, timeouts, and failures in multi-agent workflows. Use when dealing with external model timeouts, API failures, partial success, user cancellation, or graceful degradation. Trigger keywords - "error", "failure", "timeout", "retry", "fallback", "cancelled", "graceful degradation", "recovery", "partial success".

task-orchestration

241

MadAppGang

Track progress in multi-phase workflows with Tasks system. Use when orchestrating 5+ phase commands, managing iteration loops, tracking parallel tasks, or providing real-time progress visibility. Trigger keywords - "phase tracking", "progress", "workflow", "multi-step", "multi-phase", "tasks", "tracking", "status".

multi-agent-coordination

241

MadAppGang

Coordinate multiple agents in parallel or sequential workflows. Use when running agents simultaneously, delegating to sub-agents, switching between specialized agents, or managing agent selection. Trigger keywords - "parallel agents", "sequential workflow", "delegate", "multi-agent", "sub-agent", "agent switching", "task decomposition".

performance-tracking

241

MadAppGang

Track agent, skill, and model performance metrics for optimization. Use when measuring agent success rates, tracking model latency, analyzing routing effectiveness, or optimizing cost-per-task. Trigger keywords - "performance", "metrics", "tracking", "success rate", "agent performance", "model latency", "cost tracking", "optimization", "routing metrics".

task-complexity-router

241

MadAppGang

Complexity-based task routing for optimal model selection and cost efficiency. Use when deciding which model tier to use, analyzing task complexity, optimizing API costs, or implementing tiered routing. Trigger keywords - "routing", "complexity", "model selection", "tier", "cost optimization", "haiku", "sonnet", "opus", "task analysis".

hooks-system

241

MadAppGang

Comprehensive lifecycle hook patterns for Claude Code workflows. Use when configuring PreToolUse, PostToolUse, UserPromptSubmit, Stop, or SubagentStop hooks. Covers hook matchers, command hooks, prompt hooks, validation, metrics, auto-formatting, and security patterns. Trigger keywords - "hooks", "PreToolUse", "PostToolUse", "lifecycle", "tool matcher", "hook template", "auto-format", "security hook", "validation hook".

multi-model-validation

241

MadAppGang

Run multiple AI models in parallel for 3-5x speedup with ENFORCED performance statistics tracking. Use when validating with Grok, Gemini, GPT-5, DeepSeek, MiniMax, Kimi, GLM, or Claudish proxy for code review, consensus analysis, or multi-expert validation. NEW in v3.2.0 - Direct API prefixes (mmax/, kimi/, glm/) for cost savings. Includes dynamic model discovery via `claudish --top-models` and `claudish --free`, session-based workspaces, and Pattern 7-8 for tracking model performance. Trigger keywords - "grok", "gemini", "gpt-5", "deepseek", "minimax", "kimi", "glm", "claudish", "multiple models", "parallel review", "external AI", "consensus", "multi-model", "model performance", "statistics", "free models".

model-tracking-protocol

241

MadAppGang

MANDATORY tracking protocol for multi-model validation. Creates structured tracking tables BEFORE launching models, tracks progress during execution, and ensures complete results presentation. Use when running 2+ external AI models in parallel. Trigger keywords - "multi-model", "parallel review", "external models", "consensus", "model tracking".

hierarchical-coordinator

241

MadAppGang

Prevent goal drift in long-running multi-agent workflows using a coordinator agent that validates outputs against original objectives at checkpoints. Use when orchestrating 3+ agents, multi-phase features, complex implementations, or any workflow where agents may lose sight of original requirements. Trigger keywords - "hierarchical", "coordinator", "anti-drift", "checkpoint", "validation", "goal-alignment", "decomposition", "phase-gate", "shared-state", "drift detection".

github-release-management

215

proffesor-for-testing

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

qe-cicd-pipeline-qe-orchestrator

215

proffesor-for-testing

Orchestrate quality engineering across CI/CD pipeline phases. Use when designing test strategies, planning quality gates, or implementing shift-left/shift-right testing.

qe-github-release-management

215

proffesor-for-testing

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

CI/CD Pipeline QE Orchestrator

215

proffesor-for-testing

Orchestrate quality engineering across CI/CD pipeline phases. Use it when designing test strategies, planning quality gates, or implementing shift-left and shift-right testing.

sparc-methodology

215

proffesor-for-testing

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

todowrite-orchestration

132

Microck

Track progress in multi-phase workflows with TodoWrite. Use when orchestrating 5+ phase commands, managing iteration loops, tracking parallel tasks, or providing real-time progress visibility. Trigger keywords - "phase tracking", "progress", "workflow", "multi-step", "multi-phase", "todo", "tracking", "status".

task-dependency-patterns

97

yonatangross

CC 2.1.16 Task Management patterns with TaskCreate, TaskUpdate, TaskGet, TaskList tools. Decompose complex work into trackable tasks with dependency chains. Use when managing multi-step implementations, coordinating parallel work, or tracking completion status.

memory-fabric

97

yonatangross

Knowledge graph memory orchestration - entity extraction, query parsing, deduplication, and cross-reference boosting. Use when designing memory orchestration.

agent-orchestration

97

yonatangross

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.

Data Pipeline Testing

71

PramodDutta

Testing data pipelines including ETL validation, data quality checks, pipeline orchestration testing, and data lineage verification.

dag-dynamic-replanner

43

curiositech

Modifies DAG structure during execution in response to failures, new requirements, or runtime discoveries. Supports node insertion, removal, and dependency rewiring. Activate on 'replan dag', 'modify workflow', 'add node', 'remove node', 'dynamic modification'. NOT for initial DAG building (use dag-graph-builder) or scheduling (use dag-task-scheduler).

dag-task-scheduler

43

curiositech

Wave-based parallel scheduling for DAG execution. Manages execution order, resource allocation, and parallelism constraints. Activate on 'schedule dag', 'execution waves', 'parallel scheduling', 'task queue', 'resource allocation'. NOT for building DAGs (use dag-graph-builder) or actual execution (use dag-parallel-executor).

dag-result-aggregator

43

curiositech

Combines and synthesizes outputs from parallel DAG branches. Handles merge strategies, conflict resolution, and result formatting. Activate on 'aggregate results', 'combine outputs', 'merge branches', 'synthesize results', 'fan-in'. NOT for execution (use dag-parallel-executor) or scheduling (use dag-task-scheduler).

dag-executor

43

curiositech

End-to-end DAG execution orchestrator that decomposes arbitrary tasks into agent graphs and executes them in parallel. The intelligence layer that makes DAG Framework operational.

dag-parallel-executor

43

curiositech

Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination. Activate on 'execute dag', 'parallel execution', 'concurrent tasks', 'run workflow', 'spawn agents'. NOT for scheduling (use dag-task-scheduler) or building DAGs (use dag-graph-builder).

dag-context-bridger

43

curiositech

Manages context passing between DAG nodes and spawned agents. Handles context summarization, selective forwarding, and token budget optimization. Activate on 'bridge context', 'pass context', 'summarize context', 'context management', 'agent context'. NOT for execution (use dag-parallel-executor) or aggregation (use dag-result-aggregator).

dag-dependency-resolver

43

curiositech

Validates DAG structures, performs topological sorting, detects cycles, and resolves dependency conflicts. Uses Kahn's algorithm for optimal execution ordering. Activate on 'resolve dependencies', 'topological sort', 'cycle detection', 'dependency order', 'validate dag'. NOT for building DAGs (use dag-graph-builder) or scheduling execution (use dag-task-scheduler).

dag-graph-builder

43

curiositech

Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and creates optimal execution plans. Activate on 'build dag', 'create workflow graph', 'decompose task', 'execution graph', 'task graph'. NOT for simple linear tasks or when an existing DAG structure is provided.

rlm-orchestrator

42

belumume

Implement RLM-style (Recursive Language Model) orchestration for complex tasks. This skill should be used when facing large context requirements, multi-part tasks that would benefit from parallel execution, or when context rot is a concern. Automatically decomposes tasks, spawns parallel subagents, aggregates results, and iterates until completion. Inspired by the RLM research paper (arXiv:2512.24601).

apache-airflow-orchestration

40

manutej

Complete guide for Apache Airflow orchestration including DAGs, operators, sensors, XComs, task dependencies, dynamic workflows, and production deployment

kubernetes-orchestration

40

manutej

Comprehensive guide to Kubernetes container orchestration, covering workloads, networking, storage, security, and production operations

langchain-orchestration

40

manutej

Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration

coherence-engine

30

SimHacker

The LLM as consistency maintainer and orchestrator

mooco

30

SimHacker

Custom orchestrator design notes and skill interface expectations

mooco-mirror

30

SimHacker

Parallel introspection for MOOCO sessions and cross-orchestrator comparison

workflow-router

18

mehdic

Determine next agent based on state machine rules. Use AFTER receiving any BAZINGA agent response to decide what to do next.

config-seeder

18

mehdic

Seed JSON configuration files into database. Use ONCE at BAZINGA session initialization, BEFORE spawning PM.

specialization-loader

18

mehdic

Compose technology-specific agent identity and patterns. Invoke before spawning agents (Developer, SSE, QA, Tech Lead, RE, Investigator) to enhance expertise based on project stack. Returns composed specialization block with token budgeting.

prompt-builder

18

mehdic

Build complete agent prompts deterministically via Python script. Use BEFORE spawning any BAZINGA agent (Developer, QA, Tech Lead, PM, etc.).

langgraph-workflows

18

LangConfig

Expert guidance for designing LangGraph state machines and multi-agent workflows. Use when building workflows, connecting agents, or implementing complex control flow in LangConfig.

Orchestration Planner

17

daffy0208

Plan multi-step workflows using capability graph and Codex-powered goal decomposition with HTN-style hierarchical task planning.