How does the skill access my voice records?

The skill includes a Python-based extractor that queries the local Typeless.app SQLite database, ensuring your data stays on your machine during processing.

Can I integrate the analysis results with Obsidian?

Yes, the skill is designed to export structured Markdown notes directly to your Obsidian vault, updating your personal habits, work modes, and preference lists automatically.

What is 'negative guidance' in the analysis report?

Negative guidance focuses on identifying 'what to stop doing.' It highlights low-value cycles, avoidance strategies, and inefficient patterns that should be eliminated to improve performance.

Does it support real-time monitoring?

It includes a Flask-based visual dashboard that provides an overview of your record statistics, peak hours, and app distribution for real-time workflow observability.

Daily AI Workflow Analyzer

Name: Daily AI Workflow Analyzer
Author: ttmouse

byttmouse

•

Productivity & Workflow

Analyzes daily voice logs to identify behavioral patterns, cognitive biases, and strategic blind spots using deep AI insights.

About

This skill transforms raw voice records from applications like WeChat or development tools into actionable strategic intelligence. It goes beyond simple summarization by diagnosing systemic thinking errors, identifying inefficient work loops, and providing 'negative guidance' on what to stop doing. By automatically extracting principles and preferences into a structured personal knowledge base, it helps users refine their workflow and build a growing repository of personal work standards and SOPs.

Key Features

31 GitHub stars
Automated voice record extraction from Typeless.app local databases
Strategic 'negative guidance' identifying specific habits to cease
Interactive visual dashboard for monitoring app usage and analysis trends
Automated knowledge base integration with Obsidian via structured Markdown
Deep cognitive bias and behavioral pattern diagnosis using AI models

Use Cases

Building a long-term personal operating system by documenting work preferences
Extracting actionable development rules from voice-recorded coding sessions
Refining communication styles by analyzing patterns in chat log records

About

Key Features

31 GitHub stars
Automated voice record extraction from Typeless.app local databases
Strategic 'negative guidance' identifying specific habits to cease
Interactive visual dashboard for monitoring app usage and analysis trends
Automated knowledge base integration with Obsidian via structured Markdown
Deep cognitive bias and behavioral pattern diagnosis using AI models

Use Cases

Building a long-term personal operating system by documenting work preferences
Extracting actionable development rules from voice-recorded coding sessions
Refining communication styles by analyzing patterns in chat log records