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Agentic Workflow System

by @mashirops

Enables the Agentic Workflow (Kanban + Heartbeat + QA Subagent). Use this when instructed to set up a continuous, asynchronous task system for any agent.

Versionv1.0.0
Downloads1,210
TERMINAL
clawhub install agentic-workflow

πŸ“– About This Skill


name: agentic-workflow description: Enables the Agentic Workflow (Kanban + Heartbeat + QA Subagent). Use this when instructed to set up a continuous, asynchronous task system for any agent.

Agentic Workflow (Kanban & Heartbeat System)

This skill enables an OpenClaw agent to operate continuously in the background using a State Machine (Kanban board) driven by heartbeats, and ensures high-quality output through a Maker-Checker (QA subagent) verification loop.

Core Components

1. The Task Board (TASK_BOARD.yaml): The single source of truth for all tasks. 2. The Heartbeat (HEARTBEAT.md): The cron-engine that reads the board and executes tasks without user intervention. 3. The Checker (QA Subagent): The sessions_spawn mechanism used to verify results before showing them to the user.

Implementation Steps (How to install this for an agent)

When a user asks you to "set up the task system" or "agentic workflow", follow these steps in their workspace:

1. Create TASK_BOARD.yaml

Create this file in the workspace root:

# Master Task Board

Status Enum: TODO, IN_PROGRESS, QA_REVIEW, DONE, BLOCKED

current_sprint: active: false focus: "General"

tasks: - id: T-001 title: "Example Task" status: TODO created_at: "YYYY-MM-DD" description: "What needs to be done." history: []

2. Update HEARTBEAT.md

Ensure the agent's HEARTBEAT.md contains the following Executor instruction (usually at the top or highest priority):

### Task Board Executor (Highest Priority)
Trigger: Every heartbeat
Action:
1. Read TASK_BOARD.yaml.
2. If a task is IN_PROGRESS, continue its next step and update the history in YAML.
3. If no IN_PROGRESS, pick the highest priority TODO task, set to IN_PROGRESS, and begin.
4. When a task step yields a deliverable, set status to QA_REVIEW. Use sessions_spawn(runtime="subagent") to spawn a strict QA Checker agent. Give it the original goal and the output.
5. If the QA Checker approves, set status to DONE and notify the user. If it fails, fix the issue. If it fails 3 times, set to BLOCKED and notify the user.
6. If everything is running smoothly or waiting, DO NOT message the user. Reply HEARTBEAT_OK to stay silent.

The Maker-Checker Loop (Crucial!)

When you (the Maker) finish a piece of work (e.g., generating a PDF, writing a script), you must not immediately tell the user. Instead, you must spawn a subagent to act as the Checker.

Example sessions_spawn payload for the Checker:

{
  "task": "You are a strict QA inspector. Review this output: [Output]. Does it perfectly meet these requirements: [Requirements]? Reply ONLY with 'PASS' or a list of specific flaws to fix.",
  "runtime": "subagent",
  "mode": "run",
  "agentId": "distiller"  // Or the default subagent
}

Golden Rules for the Agent

  • Silence is Golden: Never message the user just to say "I am working on step 2." Only message them when a task hits DONE or BLOCKED.
  • Read Before Acting: Always read TASK_BOARD.yaml upon waking up (heartbeat) to know your current state.
  • Self-Correction: Let the QA subagent hurt your feelings. Fix the code/output internally before bothering the human.