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akievo

Akievo

by Akievo · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install akievo
Description
Persistent project planning for AI agents. Create, manage, and track long-term goals using structured Kanban boards that survive session resets.
README (SKILL.md)

Akievo — Agent Plan Mode

You have access to Akievo, a structured project management system. Use it as your persistent memory and planning layer for long-term goals. Akievo boards survive session resets — they are your source of truth.

Core Principles

  1. Always check before creating. At the start of every session, call list_boards to find existing plans before creating new ones.
  2. One board per goal. Each major goal or project gets its own board. Prefix agent-created boards with [Agent] (e.g., [Agent] Launch SaaS Product).
  3. Lists are phases. Use lists to represent sequential phases or categories (e.g., "Research", "Build", "Launch", "Done").
  4. Cards are tasks. Each actionable step is a card. Include clear titles and descriptions.
  5. Respect human edits. The human may add, remove, reprioritize, or comment on cards. Always re-read the board before acting. Never undo or override human changes.

Session Start Pattern

Every time a new session begins:

  1. Call list_boards to find boards prefixed with [Agent]
  2. If a relevant board exists, call get_board with its ID to load the full state
  3. Read the board's project_memory field for context (goal, timeline, assumptions)
  4. Identify the next unblocked, incomplete task
  5. Report status to the user: what's done, what's next, any blockers

Creating a New Plan

When the user describes a new goal:

  1. Call list_workspaces to find available workspaces
  2. Use create_board_with_tasks to scaffold the entire plan in one call:
    • Break the goal into 3–6 phases (lists)
    • Each phase gets 3–8 concrete tasks (cards)
    • Add checklists for tasks with sub-steps
    • Set priorities: critical, high, medium, low
    • Set due dates when the user provides a timeline
  3. Create dependencies between tasks that have a natural order using bulk_create_dependencies
  4. Present the plan to the user and ask for feedback before proceeding

Working on Tasks

When executing on a plan:

  1. Pick the next unblocked, highest-priority incomplete card
  2. Work on it (using your other tools — coding, research, writing, etc.)
  3. Add progress updates as comments using add_comment
  4. When done, call complete_card to mark it finished
  5. If blocked, call block_card with a clear reason
  6. Move to the next task

Updating the Plan

As work progresses, the plan may need adjustment:

  • Add new tasks: create_card in the appropriate list
  • Update details: update_card to change title, description, priority, or due date
  • Reorder: move_card to shift tasks between phases
  • Add sub-tasks: add_checklist_item for granular steps
  • Never delete cards without asking the user first

Progress Reporting

When the user asks for a status update:

  1. Call get_board to get current state
  2. Count completed vs total cards per list
  3. Highlight blocked items and their reasons
  4. Identify upcoming due dates
  5. Suggest next actions

Important Safety Rules

  • Never delete a board without explicit user confirmation
  • Never archive cards without asking
  • Always re-read the board before making changes (the human may have edited it)
  • Log your work — add comments to cards explaining what you did and why
  • Stay scoped — only modify boards you created or were explicitly asked to manage
Usage Guidance
This skill is internally coherent and appears to do what it says: manage persistent Akievo Kanban boards. Before installing, verify the Akievo service (akievo.com) is the legitimate service you expect and that the referenced repository/homepage are trustworthy. Create an API key with the minimum scopes required (prefer scoped read/write keys rather than full account-wide keys) and be prepared to revoke it if you see unexpected activity. Remember the agent may act autonomously by default — monitor initial runs and ensure the agent follows the SKILL.md rule to ask before deleting/archiving boards. If you have any doubt about the publisher, confirm the GitHub repo or company site listed in the README/skill.yaml before granting the API key.
Capability Analysis
Type: OpenClaw Skill Name: akievo Version: 1.0.0 The Akievo skill is a legitimate project management integration that allows AI agents to maintain persistent Kanban boards via a remote MCP server (mcp.akievo.com). The instructions in SKILL.md and README.md are well-structured, focusing on task organization, respecting human edits, and maintaining an audit trail through comments, with no evidence of data exfiltration, malicious execution, or prompt injection attacks.
Capability Assessment
Purpose & Capability
Name/description (persistent project planning) match the declared requirements: a single AKIEVO_API_KEY and MCP server pointing at mcp.akievo.com. Minor metadata mismatch: the top-level registry summary said 'Homepage: none' and 'Source: unknown', but the included files (README.md and skill.yaml) reference akievo.com and a GitHub repo — likely benign but worth verifying the publisher.
Instruction Scope
SKILL.md limits actions to board/list/card operations (list_boards, get_board, create_board_with_tasks, create_card, update_card, complete_card, etc.) and explicitly instructs to re-read boards and ask for human confirmation for destructive actions. It does not instruct reading local files, unrelated environment variables, or exfiltrating data to unexpected endpoints beyond the declared MCP server.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing is written to disk or downloaded during install. This is the lowest-risk install profile.
Credentials
Only a single environment variable (AKIEVO_API_KEY) is required and used as the Bearer token for the declared MCP server. That is proportionate for a service that needs read/write access to user boards. No unrelated secrets or config paths are requested.
Persistence & Privilege
The skill is not marked always:true and does not request system-level persistence. It can be invoked autonomously (default), which is expected for skills; SKILL.md includes user-confirmation rules for destructive actions but enforcement depends on the agent's runtime policy.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install akievo
  3. After installation, invoke the skill by name or use /akievo
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Akievo 1.0.0 — Initial Release - Introduces persistent project planning for AI agents with structured Kanban boards that survive session resets. - Boards are organized per goal, with lists as sequential phases and cards as actionable tasks. - Outlines robust workflows for session startup, goal planning, task execution, plan updating, and progress reporting. - Emphasizes respecting human edits, requiring confirmation before deleting boards or cards, and maintaining clear logs of agent actions. - Integration requires an AKIEVO_API_KEY for secure API access.
Metadata
Slug akievo
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Akievo?

Persistent project planning for AI agents. Create, manage, and track long-term goals using structured Kanban boards that survive session resets. It is an AI Agent Skill for Claude Code / OpenClaw, with 141 downloads so far.

How do I install Akievo?

Run "/install akievo" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Akievo free?

Yes, Akievo is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Akievo support?

Akievo is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Akievo?

It is built and maintained by Akievo (@akievo); the current version is v1.0.0.

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