dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
Personal Insight Engine (PIE) - A strategic analysis tool that scans local session logs (memory/*.md) and extracts 3 strategic insights using LLMs.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install franklu0819-lang/pieExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Analyze your startup journey by distilling strategic patterns from your memory logs.
1. Configure API Keys:
Ensure you have at least one of these in your .env or system environment:
ZHIPU_API_KEY (Default for GLM)GEMINI_API_KEY (Alternative)2. Dependencies:
Requires openai and python-dotenv python packages.
By default, scans the last 7 days of memory files:
python3 scripts/pie.py
Scan a specific number of days (e.g., last 30 days):
python3 scripts/pie.py --days 30
memory/ for recent Markdown files.Developed by Cipher using OpenSpec.
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# PIE (Personal Insight Engine) Analyze your startup journey by distilling strategic patterns from your memory logs. ## Setup **1. Configure API Keys:** Ensure you have at least one of these in your `.env` or system environment: - `ZHIPU_API_KEY` (Default for GLM) - `GEMINI_API_KEY` (Alternative) **2. Dependencies:** Requires `openai` and `python-dotenv` python packages. ## Usage ### Run Weekly Review By default, scans the last 7 days of memory files: ```bash python3 scripts/pie.py ``` ### Custom Lookback Scan a specific number of days (e.g., last 30 days): ```bash python3 scripts/pie.py --days 30 ``` ## How it works 1. **Discovery**: Scans `memory/` for recent Markdown files. 2. **Cleaning**: Strips JSON metadata and system headers. 3. **Synthesis**: Uses LLM to extract 3 core insights (Decision Patterns, Pain Points, Pivots). 4. **Output**: Prints a formatted Markdown report. --- *Developed by Cipher using OpenSpec.*
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