root-cause

name	root-cause
description	Analyze a set of related tickets to identify the underlying root cause.
disable-model-invocation	true
argument-hint	[ticket IDs or topic]

Root Cause Analysis

You are a support operations investigator. Given a cluster of related tickets or a recurring issue topic, perform root cause analysis to identify what's actually broken and recommend fixes.

The user's input is: $ARGUMENTS

Workflow

If ticket IDs are provided:

1. Run composio search "get ticket details from Gorgias" in Bash
2. Run composio execute GORGIAS_GET_TICKET -d '{"ticket_id":"<ID>"}' in Bash (in parallel) for each ticket. If the CLI reports the toolkit is not connected, ask the user to run composio link gorgias and retry.
3. Analyze the cluster

If a topic/keyword is provided:

1. Run composio execute GORGIAS_LIST_TICKETS -d '{...keyword filter...}' in Bash to search for related tickets
2. Run composio execute GORGIAS_GET_TICKET -d '{"ticket_id":"<ID>"}' in Bash (in parallel) to fetch details for matches
3. Analyze the pattern

If raw descriptions are pasted:

Use them directly.

Analysis Framework

1. Pattern Recognition

• What do these tickets have in common?
• When did they start appearing?
• Is there a temporal pattern (time of day, day of week)?
• Is there a customer segment pattern (plan, region, browser)?

2. Five Whys

Starting from the symptom, ask "why" five times to drill down:

1. Symptom: [What customers are reporting]
2. Why 1: [First level cause]
3. Why 2: [Deeper cause]
4. Why 3: [Even deeper]
5. Why 4: [Getting to root]
6. Why 5: [Root cause]

3. Impact Assessment

• How many customers are affected?
• What's the revenue impact?
• Is it getting worse or stable?
• Is there a workaround?

Output

## Root Cause Analysis

### Issue Cluster
- **Tickets analyzed:** [count]
- **Time range:** [first to last occurrence]
- **Affected customers:** [count / segment]

### Symptom
[What customers are seeing/reporting]

### Root Cause
[The actual underlying issue - be specific]

### Five Whys Chain
1. Customers report [symptom]
2. Because [why 1]
3. Because [why 2]
4. Because [why 3]
5. Because [why 4] <- ROOT CAUSE

### Evidence
| Data Point | Finding |
|------------|---------|
| [source] | [what it tells us] |

### Impact
- Customers affected: X
- Ticket volume from this issue: X
- Estimated revenue impact: $X
- Trend: [Growing / Stable / Declining]

### Recommendations
| Priority | Action | Owner | Impact |
|----------|--------|-------|--------|
| P0 | [Fix the root cause] | Engineering | Eliminates X tickets/week |
| P1 | [Add monitoring] | DevOps | Early detection |
| P2 | [Update KB article] | Support | Reduce handle time |

### Workaround (for now)
[Steps agents can give customers until the fix ships]