/install ai-productivity-stack
AI Productivity Stack
Overview
AI Productivity Stack is a workflow design workshop that helps users build a personal AI-enhanced productivity system. It guides users through auditing their current tasks, identifying where AI adds genuine value, and constructing a stack for email, writing, research, scheduling, and task management — with "human-in-the-loop" checkpoints to prevent over-automation.
This skill focuses on personal productivity, not automating away jobs or responsibilities that require human judgment.
When to Use
Use this skill when the user asks to:
- Use AI for productivity
- Build an AI workflow
- Automate tasks with AI
- Find AI tools for getting things done
- Work faster with AI
Trigger phrases: "AI for productivity", "Build an AI workflow", "Automate with AI", "AI tools for getting things done", "Work faster with AI"
Workflow
Step 1 — Greet and Assess
Acknowledge the user's productivity goals. Ask:
- What does a typical workday or week look like?
- What tools do they currently use?
- What are their biggest productivity pain points? (email overload, writer's block, research time, meeting prep, task prioritization)
- How comfortable are they with trying new tools?
Step 2 — Task Audit
Guide the user through listing their regular tasks. For each task, assess:
- Frequency: How often does it occur?
- Time consumed: How long does it take?
- Cognitive load: Is it draining or mechanical?
- AI fit: Could AI help? (high/medium/low/none)
Categorize tasks into:
- High AI fit: Drafting, summarizing, brainstorming, formatting, transcribing
- Medium AI fit: Research, scheduling, note organization, first-pass editing
- Low/none AI fit: Final decision-making, sensitive communication, creative direction, relationship building
Step 3 — Design the AI Touchpoints
For high and medium-fit tasks, design specific AI touchpoints:
Email:
- AI drafts responses to routine emails
- Human reviews, personalizes, and sends
- Never AI-send without human review for important communications
Writing:
- AI generates outlines and first drafts
- Human provides voice, examples, and final polish
- AI helps with editing and clarity, not authorship
Research:
- AI summarizes long articles and reports
- Human verifies key facts and reads primary sources for critical decisions
- AI generates questions to guide deeper reading
Scheduling and Task Management:
- AI suggests time blocks based on priorities
- Human approves and adjusts
- AI generates meeting agendas; human owns the outcomes
Step 4 — Build the Stack
Recommend a lightweight, integrated stack based on the user's tools and comfort level:
- Minimal stack: One AI chatbot + existing tools (lowest friction)
- Balanced stack: AI chatbot + one specialized tool (e.g., meeting transcriber, research assistant)
- Advanced stack: Multiple AI tools with clear role separation
Emphasize: start with the minimal stack. Add tools only when a clear gap exists.
Step 5 — Human-in-the-Loop Checkpoints
Establish rules for when the human must be involved:
- Never fully automate: Sensitive emails, performance reviews, conflict resolution, any communication with emotional weight
- Always review: Anything sent externally, factual claims, data analysis
- Human owns: Final decisions, creative direction, relationship management
Create a personal "AI boundary list" — tasks the user decides AI will never touch.
Step 6 — Summarize and Exit
Recap the user's personalized productivity audit and recommended stack. Provide:
- A staged implementation plan (start with highest-impact, lowest-risk change)
- A reminder to review the stack after 2-4 weeks of use
- Suggest related skills: Prompt Library Builder for reusable productivity prompts, AI Decision Framework for prioritization
Safety & Compliance
- Focuses on personal productivity, not automating away jobs or responsibilities
- Does not encourage AI use where human judgment is critical (e.g., final editing of important communications)
- Does not recommend tools that violate platform terms of service
- Emphasizes human-in-the-loop for all external-facing work
- This is a descriptive prompt-flow skill with zero code execution, zero network calls, and zero credential requirements
Acceptance Criteria
- User describes their work/tasks; output includes a task-by-task AI fit assessment
- A recommended stack is provided at an appropriate complexity level for the user
- Human-in-the-loop checkpoints are explicitly defined
- A staged implementation plan is provided
- Does not recommend fully automating sensitive or relationship-critical tasks
Examples
Example 1: Knowledge Worker
User says: "I spend too much time on email and meeting notes. How can AI help?"
Skill guides: Audit typical week. Identify high-fit tasks (email drafting, meeting summarization). Design touchpoints: AI drafts, human reviews. Recommend minimal stack: AI chatbot for drafting + existing note app. Set boundary: human reviews all external emails. Provide staged plan: week 1 — email drafting; week 2 — meeting notes; week 3 — review and adjust.
Example 2: Freelancer Overwhelmed by Admin
User says: "I'm a freelancer drowning in admin tasks. Can AI save me?"
Skill guides: List admin tasks (invoicing, client communication, scheduling, proposal writing). Assess AI fit for each. Design touchpoints: AI drafts proposals from templates, AI suggests schedule blocks, AI generates invoice reminders. Emphasize: client relationships stay human. Recommend balanced stack. Create boundary list.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install ai-productivity-stack - 安装完成后,直接呼叫该 Skill 的名称或使用
/ai-productivity-stack触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Ai Productivity Stack 是什么?
Design a personal AI-enhanced workflow that saves time without creating tech debt. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 37 次。
如何安装 Ai Productivity Stack?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-productivity-stack」即可一键安装,无需额外配置。
Ai Productivity Stack 是免费的吗?
是的,Ai Productivity Stack 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Ai Productivity Stack 支持哪些平台?
Ai Productivity Stack 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Ai Productivity Stack?
由 haidong(@harrylabsj)开发并维护,当前版本 v1.0.0。