Running one agent is straightforward. Running five that depend on each other is where things fall apart. One agent finishes before the other starts, results vanish between handoffs, and a single failure cascades into a full restart. Orchestration skills handle the coordination layer so you can focus on what each agent actually does.
These six cover the full stack: subtask decomposition, routing, parallel execution, retry logic, and event-driven architectures. All run inside agents like Claude Code, Codex, and Cursor.
What to look for
Handoff reliability matters most. When Agent A finishes and passes context to Agent B, nothing should get dropped. The best orchestration skills track state between agents and preserve context across handoffs without requiring you to wire that plumbing yourself.
Failure handling separates toy demos from production systems. A skill that retries transient errors, skips permanently failed branches, and preserves completed work means you don’t lose an hour of parallel results because one task timed out.
Dependency awareness is the baseline. If Task C depends on Tasks A and B, the skill should know that. Skills that understand dependency graphs run independent work in parallel and block dependent work until inputs are ready.
Then there’s the routing question. In systems with multiple specialized agents, something needs to decide which agent handles which task. Manual routing breaks at scale. Good orchestration skills match task types to agent capabilities automatically.
Top agent skills for multi-agent orchestration
1. OpenForgeAI
OpenForgeAI is the heaviest orchestration skill in the directory. Four production components: an EventBus for pub/sub agent communication, a SagaCoordinator for rollback-safe multi-step workflows, a Skill Registry for auto-discovery, and a ContractValidator that catches broken wiring at deploy time.
SagaCoordinator is the reason to install it. Multi-step agent workflows fail midway constantly — an API is down, a dependency returns bad data, a rate limit kicks in. It rolls back completed steps in the right order so you don’t end up with half-executed state. Built from a live SaaS product, ships with 17 documented laws from real production failures.
Compatible with: Claude Code, Codex, Universal
Category: Orchestration
Install: pip install openforgeai
2. Multi-Agent Router
Multi-Agent Router solves one problem: given an incoming task, which agent should handle it? It evaluates task type, required tools, and agent availability, then routes accordingly. Also manages handoffs mid-task and aggregates results from parallel calls.
If you’ve got three or four specialized agents — research, coding, writing — and you’re still manually deciding who gets what, this is the fix. Routing logic adapts based on what each agent is equipped to handle.
Compatible with: Claude Code, Codex, Universal
Category: Orchestration
Install: gh skill install VoltAgent/awesome-agent-skills/multi-agent-router
3. Task Decomposer
Task Decomposer sits upstream of execution. Hand it “build the user dashboard” and it returns twelve concrete subtasks with dependencies, estimated effort, and acceptance criteria.
Other planning skills produce flat lists. This one maps which tasks block which, so a parallel executor or router can schedule work correctly. That dependency graph is the whole point — without it, you’re guessing at execution order.
Compatible with: Claude Code, Codex, Gemini CLI, Cursor, Universal
Category: Orchestration
Install: gh skill install wshobson/agents/task-decomposer
4. Parallel Executor
Name says it all. Parallel Executor runs multiple independent agent tasks concurrently with dependency graph awareness, manages concurrency limits, and aggregates results.
Where it earns its keep: partial failure handling. Fire off ten research tasks, three fail — it keeps the seven successful results and only retries the failures. Without this, a single timeout means re-running the entire batch.
Compatible with: Claude Code, Codex, Universal
Category: Orchestration
Install: gh skill install wshobson/agents/parallel-executor
5. Superpowers Dev Workflow
Superpowers Dev Workflow is opinionated. Seven phases: ideation, spec writing, planning, subagent spawning, TDD, code review, merge. Each phase has a quality gate before the next one starts.
The orchestration happens at the subagent spawning phase — it creates specialized subagents for research, implementation, and review, then coordinates them through the rest. Enforces spec-before-code discipline. Agents plan before they build. If you’ve watched an agent burn 20 minutes coding the wrong thing, you get why that matters.
Compatible with: Claude Code
Category: Orchestration
Install: gh skill install obra/superpowers
6. Retry Handler
Retry Handler is a supporting skill — it makes everything else on this list more reliable. Exponential backoff, jitter, circuit breaker integration. Configure per-error-type policies: transient failures retry, permanent failures don’t. It surfaces telemetry so you can tune retry behavior over time.
API calls in multi-agent systems fail constantly. Rate limits, network blips, cold starts. Without structured retry logic, those failures propagate up the chain and take down entire runs. Retry Handler absorbs them at the source.
Compatible with: Claude Code, Codex, Cursor
Category: Orchestration
Install: gh skill install VoltAgent/awesome-agent-skills/retry-handler
How to choose
Start with what breaks first.
Manually deciding which agent handles which task? Multi-Agent Router. Agents know their jobs but you need concurrency? Parallel Executor. Failures cascading and killing entire runs? Retry Handler — quickest fix on the list.
For greenfield systems, pair Task Decomposer with Multi-Agent Router. Decomposer breaks work into pieces with dependencies mapped. Router assigns each piece to the right agent. Layer in Parallel Executor when throughput matters.
OpenForgeAI bundles routing, coordination, and failure recovery into one framework. Heavier than mixing individual skills, but the components work together and SagaCoordinator alone justifies the overhead if you need rollback safety.
Superpowers is the pick when orchestration means shipping code. Narrower scope, deeper in its domain.
FAQ
Q: Can I combine multiple orchestration skills, or do they conflict? A: Most stack cleanly. A common setup is Task Decomposer for planning, Multi-Agent Router for assignment, and Parallel Executor for throughput. Retry Handler layers under any of them. OpenForgeAI is more self-contained — if you adopt its EventBus pattern, you’ll use less of the individual skills.
Q: Do these skills work with agents outside Claude Code? A: Most support Codex and Universal agent types. Task Decomposer has the broadest compatibility (five agent platforms). Superpowers is Claude Code only. Check the compatible agents list for each skill before installing.
Q: What’s the difference between orchestration skills and MCP servers for multi-agent coordination? A: MCP servers handle tool access — connecting agents to databases, APIs, and external services. Orchestration skills handle agent-to-agent coordination — who does what, in what order, and what happens when something fails. They solve different layers of the stack and work together.