[copilot-session-insights] Daily Copilot Agent Session Analysis — 2026-01-29

[github-actions[bot]]

🤖 Copilot Agent Session Analysis — 2026-01-29

Executive Summary

• Sessions Analyzed: 50
• Analysis Period: 2026-01-29
• Completion Rate: 5.13%
• Average Duration: 1.17 minutes
• Experimental Strategy: None (standard analysis)

Key Metrics

Metric	Value	Trend
Total Sessions	50	→
Successful Completions	2 (5.13%)	→
Action Required	37 (74%)	→
Skipped	9 (18%)	→
Failed/Abandoned	0 (0%)	✅
Average Duration	1.17 min	↓
Median Duration	0.03 min	↓
Loop Detection Rate	3 (23% of logs)	⚠️
Context Issues	0 (0%)	✅

📈 Session Trends Analysis

Completion Patterns

The completion trend chart reveals a consistent orchestration-focused workflow pattern. The dominance of "action_required" sessions (37 out of 50) indicates this system is designed for validation and review workflows rather than autonomous task completion. The low but stable success rate around 5% is by design, reflecting the architecture where most agents trigger subsequent reviews rather than completing end-to-end tasks.

Duration & Efficiency

The duration chart shows extremely efficient processing with most sessions completing in under 2 minutes. The significant gap between average (1.17 min) and median (0.03 min) duration indicates a small number of longer-running sessions (likely the 2 successful completions) while the majority execute rapid validation checks. Three sessions showed retry loop patterns, suggesting opportunities for improved error handling.

Success Factors ✅

Patterns associated with successful task execution:

1. Fast Validation Cycles: Sessions completing in under 2 minutes show high efficiency

   • Success rate: Fast checks enable rapid iteration
   • Example: 9 sessions completed in < 1 second

2. Specialized Agent Distribution: Multiple purpose-built agents working in parallel

   • Most active: Q (9), Scout (9), PR Nitpick Reviewer (8)
   • Pattern: Each agent has specific validation responsibilities

3. Zero Context Confusion: No clarification requests detected in analyzed logs

   • Success rate: 100% clarity in available logs
   • Example: All analyzed sessions had clear task definitions

Failure Signals ⚠️

Common indicators of inefficiency or potential issues:

1. Retry Loop Detection: 3 sessions exhibited loop patterns

   • Occurrence rate: 23% of analyzed logs
   • Example: Sessions 21467541281, 21467603631, 21467413895 showed retry patterns

2. Limited Log Coverage: Only 26% of sessions have detailed logs available

   • Impact: Constrains deep behavioral analysis
   • Recommendation: Improve log retention for better insights

3. Success Rate Below 10%: Very few end-to-end completions

   • Rate: 5.13% successful completions
   • Context: By design for orchestration workflows, but limits autonomous capability

Prompt Quality Analysis 📝

High-Quality Prompt Characteristics

Based on the 2 successful sessions and analysis of orchestration patterns:

• Specific file references: Clear paths and targets reduce ambiguity
• Defined scope: Bounded tasks with clear objectives
• Action-oriented: Direct instructions rather than open-ended requests

Example High-Quality Prompt Pattern:

Addressing comment on PR #12456
```
This prompt provides specific context (PR number), clear scope (addressing a comment), and actionable direction.

### Low-Quality Prompt Characteristics

Not observed in successful sessions, but inferred from retry loops:

- **Missing context**: Sessions requiring multiple attempts may lack sufficient background
- **Unclear objectives**: Retry patterns suggest initial instructions need refinement

## Notable Observations

### Loop Detection
- **Sessions with loops**: 3 out of 13 analyzed (23%)
- **Average loop count**: Multiple retry attempts per affected session
- **Common loop patterns**: Installation retries, dependency resolution, initialization attempts

### Tool Usage
- **Analysis limitation**: Tool invocation tracking requires deeper log parsing
- **Observed pattern**: Most sessions use standard GitHub Actions workflow tools
- **Missing tools**: Limited visibility into agent-specific tool usage from available logs

### Agent Distribution
- **Most active agents**: Q (9), Scout (9), PR Nitpick Reviewer (8), /cloclo (8), Archie (7)
- **Pattern**: Validation and review agents dominate activity
- **Notable**: Only 2 "Running Copilot coding agent" sessions - most work is review/validation

### Context Issues
- **Sessions with confusion**: 0 out of 13 analyzed (0%)
- **Clarification requests**: None detected
- **Assessment**: Available session prompts are clear and well-structured

## Actionable Recommendations

### For Users Writing Task Descriptions

1. **Be specific about file paths and locations**: Even though context confusion is low, explicit paths improve efficiency
   - Example: Use "Fix the validation logic in src/auth/validator.ts" instead of "Fix the validation"

2. **Define success criteria upfront**: Clear expected outcomes reduce iteration cycles
   - Example: "Ensure all tests pass and coverage remains above 80%"

3. **Break complex tasks into smaller steps**: Enable incremental progress tracking
   - Example: Instead of "Implement authentication", use separate tasks for each component

### For System Improvements

1. **Investigate retry loop patterns**: 23% loop detection rate warrants attention
   - Potential impact: High - reduces wasted compute and improves user experience

2. **Improve log retention and coverage**: Only 26% log availability limits analysis depth
   - Potential impact: Medium - enables better insights and debugging

3. **Consider autonomous completion pathways**: 5% success rate limits self-service capability
   - Potential impact: Medium - could reduce review bottlenecks for simple tasks

### For Tool Development

1. **Enhanced error recovery**: Address common retry scenarios proactively
   - Frequency of need: 3 sessions in current analysis
   - Use case: Installation failures, dependency resolution, API timeouts

2. **Improved log aggregation**: Centralized logging for comprehensive analysis
   - Frequency of need: Every session (currently 74% gaps)
   - Use case: Better debugging, pattern detection, performance optimization

## Trends Over Time

Comparing with historical data from the past 15 days:

- **Completion rate trend**: Stable around 5-8%, consistent with orchestration design
- **Average duration trend**: Trending downward (6.6 min → 1.2 min), showing improved efficiency
- **Retry loops**: Relatively consistent, appearing in 15-25% of analyzed logs
- **Agent activity**: Q, Scout, and PR reviewers consistently most active

### Historical Context

Over the 15-day analysis period:
- Total sessions analyzed: ~700+
- Log coverage has varied from 14% to 42%
- Success rates have remained consistently low by design
- Duration efficiency has improved significantly (from 9.8 min median to 0.03 min)

## Statistical Summary

```
Total Sessions Analyzed:     50
Successful Completions:      2 (5.13%)
Failed Sessions:            0 (0%)
Action Required Sessions:   37 (74%)
Skipped Sessions:           9 (18%)
In-Progress Sessions:       1 (2%)
Queued Sessions:            1 (2%)

Average Session Duration:   1.17 min
Median Session Duration:    0.03 min
Longest Session:           6.88 min (PR #12456 addressing)
Shortest Session:          0.00 min (queued session)

Loop Detection:            3 sessions (23% of logs)
Context Issues:            0 sessions (0%)
Tool Failures:             Not tracked in current analysis

Log Coverage:              26% (13 of 50 sessions)
Analysis Depth:            Limited by log availability

Next Steps

• Review retry loop patterns in sessions 21467541281, 21467603631, 21467413895
• Investigate opportunities to improve log retention
• Consider expanding autonomous completion capabilities for simple tasks
• Monitor trend of duration improvements over coming weeks
• Analyze tool usage patterns when more comprehensive logs available

---

Analysis generated automatically on 2026-01-29
Workflow Run: §21467595073
Analysis Type: Standard (non-experimental)

AI generated by Copilot Session Insights

• expires on Feb 5, 2026, 7:34 AM UTC

[github-actions[bot]]

This discussion was automatically closed because it expired on 2026-02-05T07:34:50.993Z.