| name | openclaw-executive-assistant-workflows |
| description | Build local-first executive assistant workflows with OpenClaw for data intake, operational memory, and communications triage |
| triggers | ["set up an OpenClaw executive assistant workflow","create a data intake review with OpenClaw","build operational memory tracking","triage emails with OpenClaw","generate daily logs and weekly summaries","set up local-first AI assistant workflows","create markdown artifacts from work residue","configure OpenClaw prompts for productivity"] |
OpenClaw Executive Assistant Workflows
Skill by ara.so — Hermes Skills collection.
This skill covers building local-first executive assistant workflows using OpenClaw patterns. The project demonstrates three core workflows: data intake review, operational memory tracking, and offline communications triage. All operations use local files and produce reviewable markdown artifacts.
What This Project Does
OpenClaw executive assistant workflows help you:
- Data Intake Review: Transform unknown files into trustworthy intake reports
- Operational Memory: Convert work residue into daily logs and weekly momentum documents
- Offline Communications Triage: Turn exported emails into prioritized action lists
All workflows are local-only with no live integrations, using copy/paste prompts and markdown outputs.
Project Structure
code-along/
├── INDEX.md
├── 01-data-intake-review/
│ ├── incoming/ # Files to inspect
│ ├── prompts/
│ │ └── intake-review.md
│ ├── outputs/
│ │ └── intake-review.md
│ └── expected/
│ └── report-outline.md
├── 02-operational-memory/
│ ├── inbox/ # Notes and work residue
│ ├── prompts/
│ │ ├── daily-log.md
│ │ └── weekly-hype.md
│ ├── outputs/
│ │ ├── daily-log.md
│ │ └── weekly-hype.md
│ └── schedule/
│ ├── cron-examples.md
│ └── heartbeat-note.md
├── 03-offline-communications-triage/
│ ├── eml/ # Exported email files
│ ├── prompts/
│ │ └── email-triage.md
│ ├── outputs/
│ │ └── email-triage.md
│ └── expected/
│ └── report-outline.md
└── mission-control/ # Optional dashboard
Workflow 1: Data Intake Review
Transform incoming files into structured reports.
Setup
cd code-along/01-data-intake-review
Usage Pattern
- Place unknown files in
incoming/
- Read the prompt template in
prompts/intake-review.md
- Run the prompt against the incoming files
- Generate
outputs/intake-review.md
Example Prompt Structure
# Data Intake Review Prompt
Review all files in the incoming/ directory and create a structured report:
## Summary
- Total files reviewed
- File types present
- Overall assessment
## File-by-File Analysis
For each file:
- Filename
- Type
- Size
- Key contents
- Recommendation (keep/archive/delete/action)
## Action Items
List any files requiring immediate attention
## Archive Candidates
List files safe to archive
Expected Output Format
# Intake Review - [DATE]
## Summary
3 files reviewed
- 1 PDF document
- 1 CSV dataset
- 1 text note
## File Analysis
### document.pdf
- **Type**: PDF proposal
- **Size**: 2.4 MB
- **Contents**: Q2 budget proposal draft
- **Recommendation**: ACTION - Review by EOD Friday
### data.csv
- **Type**: CSV dataset
- **Size**: 145 KB
- **Contents**: Customer feedback responses
- **Recommendation**: KEEP - Reference for analysis
## Action Items
1. Review document.pdf budget proposal
2. Schedule feedback analysis meeting
Workflow 2: Operational Memory
Convert daily work residue into structured logs and weekly summaries.
Setup
cd code-along/02-operational-memory
Daily Log Generation
# Daily Log Prompt
Review all notes and work artifacts in inbox/ from today.
Generate a daily log with:
## Work Completed
- Tasks finished
- Decisions made
- Problems solved
## In Progress
- Ongoing work
- Blockers encountered
## Notes for Tomorrow
- Priorities
- Follow-ups needed
## Quick Wins
- Small achievements worth noting
Weekly Summary Generation
# Weekly Hype Prompt
Review the past week's daily logs.
Create a weekly summary:
## 🎯 Goals Achieved
What got done this week
## 📈 Progress Made
Movement on larger initiatives
## 🔥 Highlights
Wins worth celebrating
## 🚀 Next Week Focus
Top 3 priorities
## 💡 Lessons Learned
Key insights from the week
Automation with Cron
Example cron configuration for daily logs:
0 17 * * * cd ~/code-along/02-operational-memory && ./generate-daily-log.sh
0 16 * * 5 cd ~/code-along/02-operational-memory && ./generate-weekly-hype.sh
Example Script
#!/bin/bash
DATE=$(date +%Y-%m-%d)
PROMPT_FILE="prompts/daily-log.md"
OUTPUT_FILE="outputs/daily-log-${DATE}.md"
echo "Generating daily log for ${DATE}..."
cp "$PROMPT_FILE" "$OUTPUT_FILE"
echo "# Daily Log - ${DATE}" >> "$OUTPUT_FILE"
Workflow 3: Offline Communications Triage
Transform exported emails into actionable reports.
Setup
cd code-along/03-offline-communications-triage
Email Export Process
Export emails to .eml format and place in the eml/ directory.
Triage Prompt Structure
# Email Triage Prompt
Review all .eml files in the eml/ directory.
Create a triage report:
## 🚨 Urgent - Respond Today
Emails requiring immediate attention
## 📋 Action Required - This Week
Emails needing response within 3-5 days
## 📖 For Review
Informational emails worth reading
## 🗑️ Low Priority
Can be archived or handled later
For each email include:
- From
- Subject
- Date
- Brief summary
- Recommended action
- Estimated time required
Expected Output
# Email Triage Report - 2026-04-25
## 🚨 Urgent - Respond Today
### Email 1
- **From**: sarah@company.com
- **Subject**: Q2 Budget Approval Needed
- **Date**: 2026-04-25 09:15 AM
- **Summary**: Budget requires sign-off before Monday meeting
- **Action**: Review and approve budget spreadsheet
- **Time**: 30 minutes
## 📋 Action Required - This Week
### Email 2
- **From**: team@project.com
- **Subject**: Design Review Feedback
- **Date**: 2026-04-24 02:30 PM
- **Summary**: Design mockups ready for review
- **Action**: Provide feedback on 3 design options
- **Time**: 45 minutes
## 📖 For Review
### Email 3
- **From**: newsletter@industry.com
- **Subject**: Weekly Industry Update
- **Date**: 2026-04-24 08:00 AM
- **Summary**: Market trends and competitor news
- **Action**: Read when available
- **Time**: 15 minutes
Mission Control Dashboard
Optional central hub for linking all artifacts.
# Mission Control
Last updated: 2026-04-25 17:00
## 📥 Latest Intake Review
[View Report](../01-data-intake-review/outputs/intake-review.md)
- 3 files processed
- 1 action item pending
## 📝 Today's Log
[View Log](../02-operational-memory/outputs/daily-log-2026-04-25.md)
- 5 tasks completed
- 2 in progress
## 📧 Email Triage
[View Report](../03-offline-communications-triage/outputs/email-triage.md)
- 1 urgent response needed
- 3 actions this week
Best Practices
Prompt Design
- Keep prompts clear and structured
- Define expected output format explicitly
- Include examples in prompt templates
- Use consistent markdown formatting
File Organization
workflow-name/
├── incoming/ # Raw inputs
├── prompts/ # Reusable prompt templates
├── outputs/ # Generated artifacts
└── expected/ # Reference outputs
Artifact Naming
Use consistent naming conventions:
daily-log-YYYY-MM-DD.md
weekly-hype-YYYY-WW.md
intake-review-YYYY-MM-DD.md
email-triage-YYYY-MM-DD.md
Workflow Execution
- Read the prompt template
- Customize for current context
- Process input files
- Generate markdown artifact
- Review and refine output
- Archive or act on results
Troubleshooting
Prompt Not Producing Expected Output
- Check that input files are in correct location
- Verify prompt includes output format specification
- Add explicit examples to prompt
- Break complex prompts into smaller steps
Missing Context in Reports
- Include date/time stamps in prompts
- Reference previous artifacts when needed
- Add context sections to prompt templates
Automation Issues
- Verify file paths in cron scripts
- Check script permissions:
chmod +x script.sh
- Test scripts manually before scheduling
- Log script output for debugging
File Format Problems
- Ensure
.eml files are properly exported
- Check markdown syntax in outputs
- Validate file encoding (UTF-8)
Integration with AI Coding Agents
This workflow integrates with AI agents by:
- Structured Prompts: Templates that agents can execute
- File-Based I/O: Clear input/output locations
- Markdown Artifacts: Reviewable, versionable outputs
- Local-First: No API dependencies
Agents can automate:
- Reading prompt templates
- Processing input directories
- Generating formatted outputs
- Updating mission control dashboard