A robust framework for decomposing, executing, and recovering complex, multi-step AI agent tasks without losing context or data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install complex-task-orchestrator
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install complex-task-orchestrator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Complex Task Orchestrator?
The Complex Task Orchestrator is a specialized orchestration layer designed to handle high-stakes AI operations that exceed standard conversational limits. It provides a structured methodology for breaking down massive tasks into manageable units, managing sub-agent lifecycles, and preventing the common pitfalls of context bloat and session instability. By integrating this into your Openclaw Skills workflow, you ensure that long-running tasks remain stable and recoverable.
This skill focuses on the technical truth of agent execution: that complex tasks require persistent logging and strategic execution patterns. Whether you are dealing with large-scale data processing or intricate multi-step engineering dependencies, the orchestrator provides the necessary guardrails to ensure successful delivery without requiring the user to repeat requirements after a system failure.
Complex Task Orchestrator Use Cases
- Researching large batches of companies or data points (20+ entities) across multiple sources.
- Executing multi-step engineering projects where 5+ steps have strict dependency chains.
- Managing high-volume data processing tasks where sub-agents might encounter timeouts.
- Preventing data loss during long-running operations that exceed 3 minutes of processing time.
- Recovering task progress automatically after a system crash or session restart using persistent logs.
How Complex Task Orchestrator Works
- Decision Entry: The orchestrator evaluates the task based on complexity, batch size (10+ items), and estimated duration to decide if full orchestration is required.
- Phase 0 Pre-recording: Before execution, the requirement, execution plan, and key parameters are written to a daily work log using the Write-Ahead Logging (WAL) principle.
- Strategy Selection: One of four strategies is chosen: Strategy A (Serial) for high dependency, Strategy B (Parallel) for independent sub-tasks, Strategy C (Batch) for 50+ items with checkpoints, or Strategy D (Hybrid).
- Execution and Monitoring: The task is executed with active context management, pruning large tool outputs to prevent token bloat.
- Checkpoint Validation: Results are written to files incrementally, and the system performs spot checks to ensure sub-agent output accuracy.
- Failure Recovery: If a sub-agent fails or the system restarts, the orchestrator reads the log and resumes from the last known checkpoint.
Complex Task Orchestrator Setup
To implement these orchestration patterns within your Openclaw Skills environment, ensure your workspace is prepared for persistent logging and file-based state management.
# Create a memory directory for task logs
mkdir -p memory/
# Recommended: Limit concurrent sub-agents based on your hardware (e.g., EC2 t3.micro)
# Set agents.defaults.subagents.maxConcurrent to 2 or 3 in your configuration.
Ensure the agent has write access to the workspace to maintain the WAL (Write-Ahead Log) files.
Complex Task Orchestrator Data Schema & Taxonomy
The orchestrator uses a structured metadata taxonomy to keep track of complex task states within Openclaw Skills.
| File Type | Purpose | Format |
|---|---|---|
memory/YYYY-MM-DD.md |
Primary work log, source requirements, and execution steps | Markdown |
checkpoint.json |
Tracks total tasks, completed items, success/failure counts, and error logs | JSON |
results.json |
Final consolidated data output to avoid session memory limits | JSON |
subagent_result_n.json |
Isolated outputs from parallel sub-agents to prevent write conflicts | JSON |
Complex Task Orchestrator Advanced Features
- Write-Ahead Logging (WAL): Every critical action is recorded before execution to ensure 100% recoverability from crashes.
- Concurrent Write Protection: Implements a 'serial-write, parallel-read' pattern to prevent data corruption in shared files like Excel or Feishu docs.
- Context Bloat Mitigation: Automatically prunes tool outputs and summarizes intermediate steps to keep the primary session responsive.
- Sub-agent Validation: Actively verifies sub-agent claims by checking file existence and content instead of relying on announce messages.
- Incremental Checkpointing: Saves progress every N items, allowing for graceful degradation and manual intervention if rate limits are hit.
SKILL.md
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