Complete feedback loop from observability insights to skill updates. Use when analyzing enhanced telemetry patterns and automatically improving skills.
Scanned 9/4/2026
Install to Claude Code
npx -y skills add NeverSight/skills_feed --skill skill-improvement-from-observability --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: skill-improvement-from-observability
description: Complete feedback loop from observability insights to skill updates. Use when analyzing enhanced telemetry patterns and automatically improving skills.
---
# Skill Improvement from Observability
**The Self-Improvement Loop**: Enhanced Telemetry → Pattern Analysis → Skill Updates → Better Performance
## Data Source
Primary: `{job="claude_code_enhanced"}` in Loki (from enhanced-telemetry hooks)
## Workflow
### 1. Collect Observability Insights
Use observability-analyzer with enhanced telemetry:
```logql
# Session analytics
{job="claude_code_enhanced", event_type="session_end"} | json
# Error patterns
{job="claude_code_enhanced", event_type="tool_result", status="error"} | json
# Tool sequences
{job="claude_code_enhanced", event_type="tool_call"} | json
# Prompt patterns
{job="claude_code_enhanced", event_type="user_prompt"} | json
```
### 2. Run Pattern Detection
Use observability-pattern-detector operations:
- `detect-failures` → Error patterns by tool
- `detect-tool-sequences` → Inefficient tool chains
- `detect-conversation-patterns` → User behavior insights
- `detect-context-issues` → Context management problems
- `detect-waste` → Redundant operations
### 3. Extract Actionable Patterns
Filter high-impact issues from enhanced telemetry:
**Error Analysis**:
```logql
sum by (tool, error_type) (count_over_time({job="claude_code_enhanced", event_type="tool_result", status="error"} | json [7d]))
```
**Tool Inefficiency**:
```logql
# Repeated Read→Read patterns (waste)
{job="claude_code_enhanced", event_type="tool_call"} | json | previous_tool="Read" and tool_name="Read"
```
**Context Issues**:
```logql
# Auto compaction frequency
count_over_time({job="claude_code_enhanced", event_type="context_compact", trigger="auto"} [7d])
```
### 4. Map Patterns to Skills
| Pattern | Likely Skill | Action |
|---------|--------------|--------|
| Bash command errors | bash-related skills | Add existence checks |
| File not found | file operation skills | Add path validation |
| Repeated Glob→Read | search skills | Optimize file discovery |
| High context usage | context-heavy skills | Add chunking |
| Many debugging prompts | core skills | Improve error messages |
### 5. Generate Improvement Recommendations
Based on enhanced telemetry patterns:
```json
{
"improvement": {
"pattern": "File not found errors",
"occurrences": 45,
"source_query": "{job=\"claude_code_enhanced\", event_type=\"tool_result\", status=\"error\"} | json | error_type=~\".*not found.*\"",
"affected_skills": ["file-operations"],
"recommendation": "Add file existence check before Read/Edit operations",
"implementation": "Add pathlib.Path(file).exists() check",
"priority": "high",
"expected_impact": "Reduce errors by 80%"
}
}
```
### 6. Track Effectiveness
After improvements deployed, measure:
```logql
# Before vs After error rates
sum(count_over_time({job="claude_code_enhanced", event_type="tool_result", status="error"} | json [7d]))
# Tool success rate improvement
sum(count_over_time({job="claude_code_enhanced", event_type="tool_result", status="success"} | json [7d])) /
sum(count_over_time({job="claude_code_enhanced", event_type="tool_result"} | json [7d]))
```
## Example Improvement Flows
### Flow 1: Error Reduction
```
Telemetry: "npm not found" × 45 in tool_result errors
↓
Pattern: Bash tool failures with npm commands
↓
Recommendation: Add npm availability check
↓
skill-updater applies changes
↓
Telemetry tracks: npm errors = 0 after deployment
↓
Result: ✅ 100% reduction
```
### Flow 2: Context Optimization
```
Telemetry: Auto-compaction triggered 12 times in 7 days
↓
Pattern: Large file reads accumulating tokens
↓
Recommendation: Add file chunking for large reads
↓
skill-updater applies changes
↓
Telemetry tracks: Auto-compactions = 2 after deployment
↓
Result: ✅ 83% reduction
```
### Flow 3: Tool Sequence Optimization
```
Telemetry: Glob→Read→Glob→Read pattern 89 times
↓
Pattern: Redundant file discovery
↓
Recommendation: Cache glob results within session
↓
skill-updater applies changes
↓
Telemetry tracks: Redundant glob reduced by 70%
↓
Result: ✅ Faster file operations
```
## Key Queries for Improvement Analysis
### High-Impact Errors
```logql
topk(10, sum by (tool, error_type) (count_over_time({job="claude_code_enhanced", event_type="tool_result", status="error"} | json [7d])))
```
### Session Quality Issues
```logql
# High error sessions
{job="claude_code_enhanced", event_type="session_end"} | json | error_count > 5
# Low productivity sessions (high turns, few tool calls)
{job="claude_code_enhanced", event_type="session_end"} | json | turn_count > 20 and tools_used < 5
```
### Tool Efficiency
```logql
# Tool usage distribution
sum by (tool) (count_over_time({job="claude_code_enhanced", event_type="tool_call"} | json [7d]))
# Error rate by tool
sum by (tool) (count_over_time({job="claude_code_enhanced", event_type="tool_result", status="error"} | json [7d])) /
sum by (tool) (count_over_time({job="claude_code_enhanced", event_type="tool_result"} | json [7d]))
```
### User Behavior Insights
```logql
# Prompt pattern trends
sum by (pattern) (count_over_time({job="claude_code_enhanced", event_type="user_prompt"} | json [7d]))
# Debugging frequency (indicates pain points)
count_over_time({job="claude_code_enhanced", event_type="user_prompt", pattern="debugging"} [7d])
```
## Integration with Ecosystem
Uses existing skills:
- **observability-analyzer**: Query enhanced telemetry data
- **observability-pattern-detector**: Detect improvement patterns
- **skill-updater**: Apply safe improvements
- **review-multi**: Validate changes
- **skill-tester**: Regression testing
- **enhanced-telemetry**: Source of all observability data
## Safety Classification
**Auto-Apply Safe**:
- ✅ Adding existence checks
- ✅ Adding error handling
- ✅ Improving error messages
- ✅ Updating documentation
- ✅ Adding validation
**Require Review**:
- ❌ Changing core logic
- ❌ Modifying APIs
- ❌ Removing functionality
- ❌ Changing data structures
## Effectiveness Metrics
Track improvement success:
```logql
# Calculate error reduction percentage
(before_errors - after_errors) / before_errors * 100
# Track pattern elimination
count_over_time({job="claude_code_enhanced"} | json | <pattern_filter> [7d])
```
Report format:
```json
{
"improvement_id": "file-existence-check",
"deployed": "2025-11-27",
"before_errors": 45,
"after_errors": 2,
"reduction_percent": 95.6,
"status": "successful"
}
```
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