akievo

What This Skill Does

Akievo acts as the persistent project management layer for OpenClaw AI agents. It enables agents to move beyond transient session memory by providing a structured, Kanban-style interface that survives session resets. With Akievo, agents treat project boards as their 'source of truth,' allowing them to maintain complex, multi-step project plans, track task dependencies, and communicate progress effectively over long durations. It forces the agent to adopt an architectural approach to work, emphasizing planning, phase-based progression, and clear task management.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/akievo/akievo

Use Cases

• Long-term Software Development: Manage complex coding projects that span multiple days or weeks, ensuring the agent remembers where it left off.
• Content Calendars: Coordinate multi-step content production workflows, from drafting and editing to final publication.
• Research Projects: Break down deep-dive research tasks into specific phases, tracking findings through organized board lists.
• Agent Autonomy: Empower agents to self-organize, reprioritize tasks based on blockers, and provide status updates without requiring constant human guidance.

Example Prompts

1. "I need to build a landing page for my new startup. Please create an [Agent] board for this project with phases for research, design, coding, and deployment."
2. "Show me the status of my current project. Which tasks are blocked, and what should I be focusing on next?"
3. "I've finished the initial database schema design. Update the Akievo board to reflect that this task is complete and move the 'Write API documentation' task to 'In Progress'."

Tips & Limitations

• Always verify: When starting a new session, always ask the agent to call list_boards to sync with existing project states.
• Respect Human Input: Remember that the human user is the final authority. If a human modifies a board manually, the agent must treat those changes as final and avoid overriding them.
• Granularity: While cards can have checklists, avoid making cards too broad. Breaking a large goal into 3-6 distinct lists with clear task ownership makes the agent significantly more reliable.
• Limitations: The agent must be explicitly reminded to use the tool. If you notice the agent forgetting its place in a workflow, remind it to check its Akievo board state.