Mac for Business Knowledge Manager

A personal knowledge management system that combines Zettelkasten methodology with business automation, managing IT Solution Manager and General Affairs Manager tasks while organizing knowledge systematically.

What This Skill Does

This skill helps you work with a sophisticated knowledge management and business automation system that:

Instructions for AI Agent

1. Initial Environment Setup

When setting up the project environment:

```bash

Create Python virtual environment

python3 -m venv .venv

source .venv/bin/activate

Install dependencies

pip install -r requirements.txt

Copy environment template and configure

cp env.example env.local

```

After copying `env.example` to `env.local`, inform the user they need to configure these critical environment variables:

**Never commit `env.local`, token files (`token*.json`), or token cache files (`token_cache*.bin`) to version control.**

2. Understanding the Zettelkasten Structure

When navigating the knowledge base, recognize this hierarchy:

When creating or modifying notes, ensure they follow the progressive elaboration pattern and maintain appropriate cross-references using Obsidian wiki-link syntax `[[Note Title]]`.

3. Business Folders Organization

The project maintains these business-focused directories:

4. Running Daily Report Agent

To generate daily business reports:

```bash

Generate report for today

python3 Agents/daily_report/main.py

Generate report for specific date

python3 Agents/daily_report/main.py 2025-07-24

```

The agent will:

1. Authenticate with Microsoft Graph API using MSAL

2. Collect Teams messages and channel posts

3. Retrieve sent emails

4. Discover new OneDrive files and summarize with Gemini

5. Fetch Google Calendar events

6. Generate a comprehensive Markdown report in `80-業務日報/`

**If authentication fails**, check token cache files and ensure `env.local` contains valid Microsoft credentials.

5. Running Clippings Sorter Agent

To process and categorize web clippings:

```bash

python3 Agents/clippings_sort/run_enhanced_clippings_sorter.py

```

The agent will:

1. Scan all Markdown files in `Clippings/`

2. Use AI (Google Gemini) to analyze content and assign categories/tags

3. Move files to appropriate category subdirectories

4. Merge similar content and create permanent notes (max 15 per category)

5. Generate category indexes and structure documentation

**Ensure Gemini API key is configured in `env.local` before running.**

6. Running Schedule Synchronization

To sync schedules with Google Calendar:

```bash

python3 Agents/schedule_updater/auto_schedule_sync.py

```

This uses service account authentication with Google Calendar API. Verify service account credentials are properly configured.

7. Backing Up to OneDrive

To create a backup copy to OneDrive:

```bash

rsync -avh --delete \

--exclude '.git' \

--exclude '.venv' \

--exclude '.obsidian' \

'/Users/ueshima/Workspace/Mac for Business/' \

'/Users/ueshima/Library/CloudStorage/OneDrive-医療法人社団　慶友会　吉田病院/Mac for Business-backup'

```

**Adjust paths according to the actual user's system configuration.**

8. Working with the Codebase

When modifying automation agents:

9. Key Dependencies to Understand

10. Important Constraints

Example Usage

**User:** "Generate today's daily report"

**Agent actions:**

1. Activate virtual environment

2. Run `python3 Agents/daily_report/main.py`

3. Monitor output for authentication issues

4. Verify report file created in `80-業務日報/YYYY-MM-DD.md`

**User:** "Process all my web clippings"

**Agent actions:**

1. Run `python3 Agents/clippings_sort/run_enhanced_clippings_sorter.py`

2. Check for Gemini API key validity

3. Monitor categorization progress

4. Verify permanent notes and indexes generated

**User:** "Set up the project from scratch"

**Agent actions:**

1. Create virtual environment and install dependencies

2. Copy `env.example` to `env.local`

3. Prompt user to configure API credentials

4. Test each agent with dry-run or minimal execution

Notes