Tutorials

# Step 1: Install
pip install openclaw

# Step 2: Set API key
export OPENCLAW_API_KEY="sk-..."

# Step 3: Run first task
openclaw run "Summarise the README of this project" --file README.md

#!/usr/bin/env bash
# daily-report.sh

REPORT=$(openclaw run \
  "Summarise progress for this project, highlight blockers, and list next steps." \
  --file /workspace/project/ \
  --format markdown)

# Send via sendmail, mailgun, or any SMTP tool
echo "$REPORT" | mail -s "Daily Project Report - $(date +%F)" team@example.com

echo "Report sent."

0 8 * * 1-5 /home/user/scripts/daily-report.sh

# .github/workflows/code-review.yml
name: AI Code Review
on: [pull_request]
jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0
      - run: pip install openclaw
      - name: Review diff
        env:
          OPENCLAW_API_KEY: ${{ secrets.OPENCLAW_API_KEY }}
        run: |
          git diff origin/${{ github.base_ref }}...HEAD > diff.patch
          openclaw run "Review this diff for bugs, security issues, and style problems. Be concise." \
            --file diff.patch --format markdown > review.md
          cat review.md

# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# Pull a model
ollama pull llama3.2

# Point OpenClaw at it
openclaw config set provider ollama
openclaw config set model llama3.2
openclaw config set base_url http://localhost:11434

# Test
openclaw run "hello world"

cat > ~/scripts/morning-assistant.sh <<'EOF'
#!/usr/bin/env bash
# morning-assistant.sh

# Gather context
WEATHER=$(curl -s "wttr.in/?format=3")
NEWS=$(curl -s "https://feeds.bbci.co.uk/news/technology/rss.xml" | grep -o '<title>[^<]*</title>' | head -10 | sed 's/<\/?title>//g')
PENDING_TASKS=$(cat ~/todo.txt 2>/dev/null | head -10)

# Ask AI to create a briefing
BRIEFING=$(printf "Weather: %s\n\nTop tech news:\n%s\n\nPending tasks:\n%s" \
  "$WEATHER" "$NEWS" "$PENDING_TASKS" | \
  openclaw run "Write a concise morning briefing (under 200 words). Be direct and actionable. Start with weather, then news highlights, then my top 3 tasks for today.")

# Deliver
openclaw telegram send "Good morning!\n\n$BRIEFING"
EOF
chmod +x ~/scripts/morning-assistant.sh

# Add to crontab
(crontab -l 2>/dev/null; echo "0 8 * * 1-5 ~/scripts/morning-assistant.sh") | crontab -

# .github/workflows/ai-code-review.yml
name: AI Code Review
on:
  pull_request:
    types: [opened, synchronize]
jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with: { fetch-depth: 0 }
      - run: pip install openclaw
      - name: Generate review
        env:
          OPENCLAW_API_KEY: ${{ secrets.OPENCLAW_API_KEY }}
        run: |
          git diff origin/${{ github.base_ref }}...HEAD > diff.patch
          openclaw run "Review this diff as a senior engineer. Flag: bugs, security issues, missing tests. Format as a GitHub-flavoured Markdown checklist." \
            --file diff.patch > review.md
      - name: Post comment
        uses: actions/github-script@v7
        with:
          script: |
            const review = require('fs').readFileSync('review.md', 'utf8');
            github.rest.issues.createComment({
              ...context.repo,
              issue_number: context.issue.number,
              body: review
            });

cat > ~/scripts/weekly-analysis.sh <<'EOF'
#!/usr/bin/env bash
set -euo pipefail
DATE=$(date +%Y-%m-%d)

# Pull data (adapt to your source)
curl -s "https://your-app.com/api/export/week.csv" \
  -H "Authorization: Bearer $API_TOKEN" \
  -o "/tmp/data-$DATE.csv"

# Analyse with OpenClaw
openclaw run \
  "Analyse this weekly CSV data. Identify the top 3 trends, \
   any anomalies or drops, and write a 3-paragraph executive summary." \
  --file "/tmp/data-$DATE.csv" \
  --model gpt-4o \
  --output "/tmp/summary-$DATE.md"

# Convert and send
pandoc "/tmp/summary-$DATE.md" -o "/tmp/summary-$DATE.html"
python3 ~/scripts/send_email.py \
  --to "team@company.com" \
  --subject "Weekly Analysis — $DATE" \
  --body "/tmp/summary-$DATE.html"

echo "Weekly analysis done for $DATE"
EOF
chmod +x ~/scripts/weekly-analysis.sh

# Every Monday at 07:30
(crontab -l 2>/dev/null; echo "30 7 * * 1 ~/scripts/weekly-analysis.sh >> ~/logs/analysis.log 2>&1") | crontab -

# tools/internal_db.py
from openclaw.tools import register_tool
import sqlite3, json

@register_tool(
    name="query_sales_db",
    description="Query the sales database. Returns JSON rows. "
                "Only accepts read-only SELECT statements."
)
def query_sales_db(sql: str) -> str:
    conn = sqlite3.connect("/data/sales.db")
    try:
        rows = conn.execute(sql).fetchall()
        cols = [d[0] for d in conn.execute(sql).description]
        return json.dumps([dict(zip(cols, r)) for r in rows])
    finally:
        conn.close()

# Load your custom tool
openclaw run "What were the top 5 products by revenue last month?" \
  --tools tools/internal_db.py \
  --model gpt-4o

# The agent will call query_sales_db() with an appropriate SELECT query,
# receive the JSON rows, and produce a natural-language answer.