Advanced Examples
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These examples show how to combine multiple data sources and handle more sophisticated automation patterns while staying practical and achievable.
Weekly GitHub Activity Summary
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The Request: “Send me a weekly summary of our GitHub activity for the development team.”
Generated Playbook:
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| # Weekly GitHub Activity Summary
Compile GitHub activity for weekly team review.
## Steps
- Fetch merged pull requests from the past week across our main repositories
- Get commit activity by team member
- Count commits per person
- Note which repositories were most active
- Identify any large pull requests or significant changes
- PRs with 20+ file changes
- New features or major refactors
- Format a weekly summary:
📊 Weekly GitHub Summary - [week of date]
**Activity:**
• [X] PRs merged across [Y] repositories
• [X] total commits from [Y] contributors
**Top Contributors:**
• @[Name] - [X commits] • [Y PRs]
• @[Name] - [X commits] • [Y PRs]
**Repository Activity:**
• [repo-name] - [X PRs] • [Y commits]
• [repo-name] - [X PRs] • [Y commits]
**Notable Changes:**
• [Brief description of major PRs or features]
**Focus Areas:**
• [Repositories or features with most activity]
- Send summary via Slack DM on Friday afternoons
## Trigger
- Run every Friday at 4:00 PM
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What this playbook does:
- Provides a simple weekly overview of development activity
- Highlights team contributions and active areas
- Keeps stakeholders informed without overwhelming detail
Key learning: This shows combining data from one tool (GitHub) to create meaningful summaries without complex analysis.
Daily Support Ticket Monitor
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The Request: “Monitor our Linear support tickets and alert me if anything urgent comes up.”
Generated Playbook:
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| # Daily Support Ticket Monitor
Track support tickets and alert for urgent issues.
## Steps
- Check Linear for new tickets created in the last 24 hours with "support" label
- Look for high-priority or urgent tickets that need immediate attention
- Count total new tickets and identify any patterns
- Multiple tickets from same customer
- Similar issues reported multiple times
- If urgent tickets found, send immediate alert:
🚨 Urgent Support Alert
**Urgent Tickets:**
• [Ticket title] - [Customer] - [Priority]
• [Brief description of issue]
**Action Needed:**
• [Suggested next steps or escalation]
- Send daily summary of all new tickets:
🎫 Daily Support Summary - [date]
**New Tickets:** [X total]
**By Priority:**
• High: [X] • Medium: [Y] • Low: [Z]
**Common Issues:**
• [Pattern if any, or "No patterns detected"]
**Status:**
• [All tickets assigned | X unassigned tickets need review]
- Post summary to #support-team channel
## Trigger
- Run daily at 9:00 AM
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What this playbook does:
- Monitors for urgent issues that need immediate attention
- Provides daily visibility into support workload
- Helps identify patterns in customer issues
Key learning: This demonstrates conditional alerting - different actions based on what’s found in the data.
Content Curation Digest
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The Request: “Help me stay updated on industry news by curating relevant articles and discussions.”
Generated Playbook:
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| # Content Curation Digest
Curate relevant industry content for weekly review.
## Steps
- Search for recent articles about [your industry/technology area]
- Use multiple sources: Google News, relevant blogs, industry publications
- Look for discussions on Reddit in relevant communities
- r/programming, r/startups, or industry-specific subreddits
- Focus on posts with high engagement (100+ upvotes)
- Filter content for relevance:
- Product updates from major companies
- New technology announcements
- Industry trends and analysis
- Create a curated weekly digest:
📰 Weekly Industry Digest - [week of date]
**Top Stories:**
• [Article title] - [Brief takeaway] [Read more →](link)
• [Article title] - [Brief takeaway] [Read more →](link)
**Community Discussions:**
• [Reddit post title] - [Key insight] [View discussion →](link)
**Worth Monitoring:**
• [Trend or development to watch]
**Quick Takes:**
• [One-liner about smaller updates]
- Send digest via Slack DM every Sunday evening
## Trigger
- Run every Sunday at 6:00 PM
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What this playbook does:
- Aggregates relevant industry content from multiple sources
- Filters for high-quality, engaging content
- Provides weekly overview without information overload
Key learning: This shows content aggregation and filtering based on simple criteria (engagement, relevance).
Practical Automation Principles
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Start with Simple Data Sources
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Focus on tools and sources you already use:
- GitHub for development activity
- Linear/Jira for project management
- Google Drive for documents
- Slack for communication
- RSS feeds or news sites for content
Keep Analysis Simple
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Avoid complex calculations and focus on:
- Counting and summarizing
- Identifying patterns and outliers
- Formatting information clearly
- Providing context and next steps
Design for Real Workflows
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Consider when and how people actually work:
- Friday afternoon summaries for weekly planning
- Morning alerts for urgent issues
- Weekend content curation for Monday reading
- End-of-day status updates for closure
Handle the Unexpected Gracefully
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Plan for common scenarios:
- No activity to report: “Quiet week - no major GitHub activity”
- Missing data: “Unable to fetch GitHub data, will retry tomorrow”
- Too much data: “High activity week - [X] PRs merged (showing top 5)”
Building More Sophisticated Playbooks
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- GitHub commits + Linear tickets for development tracking
- Support tickets + customer feedback for service monitoring
- News articles + social discussions for market intelligence
Add Simple Intelligence
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- Count occurrences and identify trends
- Compare to previous periods (more/less than last week)
- Flag outliers (unusually high/low activity)
- Group similar items for pattern recognition
Scale Communication Appropriately
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- Brief daily updates for operational awareness
- Detailed weekly summaries for planning
- Immediate alerts for urgent situations
- Archived reports for historical reference
Ready to implement these patterns? Start with Quick Start Examples or explore team-focused automation in Communication Examples.