Automated pattern recognition in Claude Code telemetry. Use when detecting failures, slowness, anomalies, trends, inefficiencies, conversation patterns, or tool sequences.
Scanned 9/2/2026
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---
name: observability-pattern-detector
description: Automated pattern recognition in Claude Code telemetry. Use when detecting failures, slowness, anomalies, trends, inefficiencies, conversation patterns, or tool sequences.
---
# Observability Pattern Detector
Automated pattern recognition and anomaly detection in Claude Code telemetry data from enhanced hooks.
## Data Source
Primary: `{job="claude_code_enhanced"}` in Loki
## Operations
### `detect-failures`
Group similar failures and identify patterns.
```logql
{job="claude_code_enhanced", event_type="tool_result", status="error"} | json
```
**Algorithm**: Group by error_type → Calculate frequency → Rank by impact.
**Output**: Failure patterns with occurrences, affected tools, first/last seen, trend.
### `detect-slowness`
Identify large response patterns (proxy for slowness).
```logql
{job="claude_code_enhanced", event_type="tool_result"} | json | response_length > 100000
```
**Algorithm**: Flag responses >100k chars → Group by tool → Identify patterns.
**Output**: Slow operations with response sizes, affected tools.
### `detect-anomalies`
Statistical anomaly detection in sessions.
```logql
{job="claude_code_enhanced", event_type="session_end"} | json | turn_count > 50
```
**Methods**: High turn count, long duration, many errors per session.
**Output**: Anomalous sessions with metrics, likely cause.
### `detect-trends`
Long-term trend analysis.
```logql
sum(count_over_time({job="claude_code_enhanced", event_type="tool_call"} [1d]))
```
**Metrics**: Tool usage trend, error rate trend, session frequency trend.
**Output**: Trends with direction (increasing/decreasing/stable), rate.
### `detect-waste`
Identify inefficiencies (redundant operations).
```logql
{job="claude_code_enhanced", event_type="tool_call"} | json | line_format "{{.tool_name}}:{{.previous_tool}}"
```
**Patterns**:
- Multiple reads of same file (Read→Read)
- Repeated failed operations
- Excessive Glob before Read
- Many small edits vs one large edit
**Output**: Waste patterns with occurrences, recommendations.
### `detect-conversation-patterns`
Analyze user prompt patterns.
```logql
sum by (pattern) (count_over_time({job="claude_code_enhanced", event_type="user_prompt"} | json [24h]))
```
**Patterns**:
- Question frequency (pattern="question")
- Debugging sessions (pattern="debugging")
- Creation tasks (pattern="creation")
- Ultrathink usage (pattern="ultrathink")
**Output**: Conversation style distribution, trends.
### `detect-tool-sequences`
Identify common tool call sequences.
```logql
{job="claude_code_enhanced", event_type="tool_call"} | json | line_format "{{.previous_tool}} → {{.tool_name}}"
```
**Common Patterns**:
- Glob → Read (file discovery)
- Read → Edit (modify after read)
- Grep → Read (search then open)
- Task → Task (parallel agents)
**Output**: Sequence frequencies, unusual patterns.
### `detect-subagent-patterns`
Analyze Task tool usage patterns.
```logql
{job="claude_code_enhanced", event_type="tool_call", tool="Task"} | json
```
**Patterns**:
- Subagent types distribution
- Parallel spawning patterns
- Subagent success rates
**Output**: Subagent usage analytics, recommendations.
### `detect-context-issues`
Identify context window problems.
```logql
{job="claude_code_enhanced", event_type="context_compact"} | json
```
**Patterns**:
- Frequent auto-compaction
- High context usage sessions
- Large response accumulation
**Output**: Context management issues, optimization suggestions.
### `detect-permission-patterns`
Analyze permission request patterns.
```logql
{job="claude_code_enhanced", event_type="permission_request"} | json
```
**Patterns**:
- Frequent permission requests
- Permission types distribution
- Permission denials
**Output**: Permission friction points, automation opportunities.
### `detect-repo-patterns`
Repository activity patterns.
```logql
sum by (repo) (count_over_time({job="claude_code_enhanced", event_type="tool_call"} | json [7d]))
```
**Patterns**:
- Most active repos
- Tool usage by repo
- Error rates by repo
**Output**: Project-level insights, cross-repo comparisons.
## Example Output
```json
{
"failure_patterns": [
{
"pattern_id": "file_not_found",
"signature": "File does not exist",
"occurrences": 23,
"affected_tools": ["Read", "Edit"],
"trend": "stable",
"recommendation": "Add file existence check before operations"
}
],
"tool_sequence_patterns": [
{
"sequence": "Glob → Read → Edit",
"occurrences": 156,
"context": "Standard file modification flow"
}
],
"conversation_patterns": [
{
"pattern": "debugging",
"percentage": 35,
"avg_turns": 12,
"common_tools": ["Bash", "Read", "Grep"]
}
],
"context_issues": [
{
"issue": "auto_compaction_frequent",
"sessions_affected": 5,
"recommendation": "Use more focused queries, split large tasks"
}
]
}
```
## Pattern Detection Queries
### Failure Patterns
```logql
# Group errors by type
sum by (error_type, tool) (count_over_time({job="claude_code_enhanced", event_type="tool_result", status="error"} | json [24h]))
# Error timeline
{job="claude_code_enhanced", event_type="tool_result", status="error"} | json | line_format "{{.timestamp}} {{.tool_name}}: {{.error_type}}"
```
### Tool Sequence Patterns
```logql
# Most common transitions
{job="claude_code_enhanced", event_type="tool_call"} | json | previous_tool != "" | line_format "{{.previous_tool}} → {{.tool_name}}"
```
### Session Anomalies
```logql
# Long sessions
{job="claude_code_enhanced", event_type="session_end"} | json | duration_seconds > 3600
# High error sessions
{job="claude_code_enhanced", event_type="session_end"} | json | error_count > 5
# High turn sessions
{job="claude_code_enhanced", event_type="session_end"} | json | turn_count > 30
```
### Context Patterns
```logql
# Auto compactions
{job="claude_code_enhanced", event_type="context_compact", trigger="auto"} | json
# High utilization
{job="claude_code_enhanced", event_type="context_utilization"} | json | context_percentage > 80
```
## Scripts
- `scripts/detect-failures.sh` - Failure pattern detection
- `scripts/detect-anomalies.sh` - Statistical anomaly detection
- `scripts/detect-trends.sh` - Trend analysis
- `scripts/detect-sequences.sh` - Tool sequence analysis
- `scripts/generate-pattern-report.sh` - Full pattern report
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