openclaw-executive-assistant-webinars

# OpenClaw Executive Assistant Webinars > Skill by [ara.so](https://ara.so) — Hermes Skills collection. ## Overview This project provides a workshop framework for building local-only executive assistant workflows using OpenClaw. It demonstrates three core patterns: 1. **Data intake review** — Turn unknown files into trustworthy intake reports 2. **Operational memory** — Convert work residue into daily and weekly momentum docs 3. **Offline communications triage** — Transform exported emails into action lists All workflows use local folders, produce reviewable markdown artifacts, and require no live integrations. ## Installation Clone the repository: ```bash git clone https://github.com/dandenney/webinars-build-your-own-executive-assistant-with-openclaw.git cd webinars-build-your-own-executive-assistant-with-openclaw ``` No dependencies required — this is a file-based workflow using OpenClaw prompts with copy/paste execution. ## Repository Structure ``` code-along/ ├── INDEX.md ├── 01-data-intake-review/ │ ├── incoming/ # Files to inspect │ ├── prompts/ │ │ └── intake-review.md │ ├── outputs/ # Generated reports │ └── expected/ │ └── report-outline.md ├── 02-operational-memory/ │ ├── inbox/ # Work notes and residue │ ├── prompts/ │ │ ├── daily-log.md │ │ └── weekly-hype.md │ ├── outputs/ │ ├── schedule/ │ │ ├── cron-examples.md │ │ └── heartbeat-note.md ├── 03-offline-communications-triage/ │ ├── eml/ # Exported email files │ ├── prompts/ │ │ └── email-triage.md │ ├── outputs/ │ └── expected/ │ └── report-outline.md └── mission-control/ # Optional dashboard ``` ## Workflow Patterns ### 1. Data Intake Review Process unknown files in a folder and generate a structured intake report. **Setup:** ```bash cd code-along/01-data-intake-review ``` **Workflow:** 1. Place files to review in `incoming/` 2. Open `prompts/intake-review.md` to see the prompt template 3. Copy the prompt and provide context about files in `incoming/` 4. Save the generated output to `outputs/intake-review.md` **Expected output structure:** - File inventory - Risk assessment - Action recommendations - Priority rankings **Example prompt pattern:** ```markdown Review all files in the incoming/ directory and create an intake report that includes: - List of all files with size and type - Security/privacy concerns - Recommended actions for each file - Overall priority assessment Format as markdown with clear sections. ``` ### 2. Operational Memory Convert scattered work notes into structured daily logs and weekly summaries. **Setup:** ```bash cd code-along/02-operational-memory ``` **Daily log workflow:** ```markdown # Daily Log Prompt Pattern Review all notes in inbox/ from today and create a daily log with: - Key accomplishments - Decisions made - Blockers encountered - Tomorrow's priorities Output to: outputs/daily-log.md ``` **Weekly summary workflow:** ```markdown # Weekly Hype Prompt Pattern Review all daily logs from this week and create a weekly summary with: - Week's highlights - Momentum indicators - Patterns observed - Next week's focus areas Output to: outputs/weekly-hype.md ``` **Automation example (cron):** ```bash # Daily log generation at 5pm 0 17 * * * /path/to/generate-daily-log.sh # Weekly summary on Friday at 4pm 0 16 * * 5 /path/to/generate-weekly-hype.sh ``` ### 3. Offline Communications Triage Process exported email files (.eml) and generate action-oriented triage reports. **Setup:** ```bash cd code-along/03-offline-communications-triage ``` **Workflow:** 1. Export emails as .eml files to `eml/` directory 2. Use the triage prompt from `prompts/email-triage.md` 3. Generate report to `outputs/email-triage.md` **Example triage prompt pattern:** ```markdown Process all .eml files in eml/ and create a triage report with: ## Urgent Actions - Emails requiring immediate response - Deadlines within 24 hours ## This Week - Items needing response this week - Grouped by topic/project ## FYI / Archive - Informational items - No action needed ## Delegatable - Items that could be handled by others For each item include: - Sender - Subject line - Key points - Recommended action ``` **Expected output:** - Categorized action items - Priority rankings - Response drafts for urgent items - Delegation opportunities ## Common Patterns ### File-Based Prompt Execution All exercises follow this pattern: ```bash # 1. Navigate to exercise directory cd code-along/01-data-intake-review # 2. Review the prompt template cat prompts/intake-review.md # 3. Provide context files # (Files already in incoming/ or inbox/ directories) # 4. Copy prompt + execute with OpenClaw # (Manual copy/paste to AI assistant) # 5. Save output # Save response to outputs/[exercise-name].md ``` ### Markdown Output Structure All outputs should be markdown files with: ```markdown # Report Title **Generated:** YYYY-MM-DD HH:MM ## Executive Summary [2-3 sentence overview] ## [Section 1] [Detailed content] ## [Section 2] [Detailed content] ## Recommendations - [ ] Action item 1 - [ ] Action item 2 ## Next Steps 1. Step one 2. Step two ``` ### Scheduling Automated Runs For operational memory workflows: ```bash # Create a simple shell script wrapper #!/bin/bash # generate-daily-log.sh WORKSPACE="/path/to/code-along/02-operational-memory" cd "$WORKSPACE" # Your OpenClaw execution command here # This could be an API call, CLI command, etc. openclaw execute \ --prompt "$(cat prompts/daily-log.md)" \ --context "inbox/" \ --output "outputs/daily-log-$(date +%Y-%m-%d).md" ``` ## Configuration ### Environment Variables If integrating with OpenClaw APIs: ```bash export OPENCLAW_API_KEY=your_api_key_here export OPENCLAW_MODEL=claude-3-5-sonnet export WORKSPACE_ROOT=/path/to/code-along ``` ### Directory Conventions Maintain this structure for each workflow: - `incoming/` or `inbox/` — Input files - `prompts/` — Reusable prompt templates - `outputs/` — Generated reports (gitignored if desired) - `expected/` — Example outputs for reference ## Troubleshooting **No outputs generated:** - Verify files exist in the input directory - Check prompt file is readable - Ensure output directory has write permissions **Reports missing sections:** - Review the prompt template for completeness - Check that all input files were accessible - Verify markdown formatting in output **Automation not running:** - Test cron syntax with `crontab -l` - Check script permissions: `chmod +x generate-*.sh` - Verify paths are absolute in cron jobs - Check cron logs: `grep CRON /var/log/syslog` **File encoding issues:** - Ensure .eml files are UTF-8 encoded - Check for special characters in filenames - Verify file extensions match expected types ## Best Practices 1. **Review before committing** — All outputs are markdown for human review 2. **Version control prompts** — Keep prompt templates in git 3. **Iterate on prompts** — Refine based on output quality 4. **Archive outputs** — Date-stamp reports for historical reference 5. **Local-first** — No API calls until you're ready to automate ## Workshop Usage To follow the webinar: ```bash # Open the walkthrough open webinar-runbook.html # Work through exercises in order cd code-along/01-data-intake-review # ... complete exercise 1 cd ../02-operational-memory # ... complete exercise 2 cd ../03-offline-communications-triage # ... complete exercise 3 ``` Each exercise builds on patterns from the previous one, demonstrating progressively sophisticated file-based AI workflows.