openclaw-executive-assistant-workflows

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

1. Place unknown files in incoming/
2. Read the prompt template in prompts/intake-review.md
3. Run the prompt against the incoming files
4. 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:

# Daily log at 5 PM
0 17 * * * cd ~/code-along/02-operational-memory && ./generate-daily-log.sh

# Weekly summary on Friday at 4 PM
0 16 * * 5 cd ~/code-along/02-operational-memory && ./generate-weekly-hype.sh

Example Script

#!/bin/bash
# generate-daily-log.sh

DATE=$(date +%Y-%m-%d)
PROMPT_FILE="prompts/daily-log.md"
OUTPUT_FILE="outputs/daily-log-${DATE}.md"

# Read prompt and process inbox
echo "Generating daily log for ${DATE}..."

# Copy prompt template
cp "$PROMPT_FILE" "$OUTPUT_FILE"

# Add date header
echo "# Daily Log - ${DATE}" >> "$OUTPUT_FILE"

# Process would happen here via AI agent
# This is a manual copy/paste workflow in the workshop

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

1. Read the prompt template
2. Customize for current context
3. Process input files
4. Generate markdown artifact
5. Review and refine output
6. 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:

1. Structured Prompts: Templates that agents can execute
2. File-Based I/O: Clear input/output locations
3. Markdown Artifacts: Reviewable, versionable outputs
4. Local-First: No API dependencies

Agents can automate:

• Reading prompt templates
• Processing input directories
• Generating formatted outputs
• Updating mission control dashboard