A strategic analysis tool that distills actionable insights from local session memory logs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pie
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 pie 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 PIE (Personal Insight Engine)?
PIE (Personal Insight Engine) is a specialized utility designed to transform raw session data into high-level strategic intelligence. By scanning local memory files within the Openclaw Skills ecosystem, it identifies recurring decision patterns, pain points, and pivots that might otherwise go unnoticed in daily workflows.
This tool is essential for developers and founders who need to maintain a high-level overview of their technical evolution and project progress. It acts as a sophisticated bridge between detailed activity logs and long-term strategic planning, ensuring that every session contributes to a broader understanding of your project's trajectory.
PIE (Personal Insight Engine) Use Cases
- Conducting weekly startup journey reviews to identify growth bottlenecks and technical hurdles.
- Analyzing long-term decision patterns over a custom 30-day lookback period.
- Identifying technical pivots and recurring pain points from session history to improve future planning.
How PIE (Personal Insight Engine) Works
- Discovery: The engine scans the designated memory/ directory for recent Markdown files containing session data.
- Cleaning: It automatically strips out JSON metadata and system headers to focus on the core narrative content.
- Synthesis: Using LLM providers like Zhipu or Gemini, the tool extracts exactly three core strategic insights based on Decision Patterns, Pain Points, and Pivots.
- Output: A formatted Markdown report is generated, providing a concise summary of the session history.
PIE (Personal Insight Engine) Setup
First, ensure you have python3 installed and configure your environment by adding your API keys to your .env file:
- ZHIPU_API_KEY (Default for GLM)
- GEMINI_API_KEY (Alternative)
Install the required Python dependencies:
pip install openai python-dotenv
Run the default analysis for the last 7 days of logs:
python3 scripts/pie.py
PIE (Personal Insight Engine) Data Schema & Taxonomy
PIE operates on a specific file structure within the Openclaw Skills environment to ensure accurate data extraction:
| Component | Description |
|---|---|
| Input Source | Markdown files (.md) located specifically in the memory/ directory. |
| Processing | LLM-driven synthesis of Decision Patterns, Pain Points, and Pivots. |
| Output Format | Formatted Markdown reports containing three distilled strategic insights. |
| Filtering | Automated removal of metadata and system headers during the cleaning phase. |
PIE (Personal Insight Engine) Advanced Features
- Customizable lookback periods using the --days flag for flexible historical analysis.
- Multi-provider LLM support, allowing seamless switching between Zhipu GLM and Google Gemini.
- Automated extraction of systemic decision-making patterns to track project evolution.
- Seamless integration with existing Openclaw Skills session logging workflows.
SKILL.md
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