[copilot-session-insights] Daily Copilot Agent Session Analysis — 2026-02-04

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Executive Summary

• Sessions Analyzed: 16 (50 fetched, 34 skipped/no logs)
• Analysis Period: February 4, 2026
• Completion Rate: 37.5% (6 successful out of 16)
• Average Duration: 58.5 minutes (overall), 6.5 minutes (successful only)
• Experimental Strategy: Temporal Analysis - Session timing patterns and hour-of-day effects

Key Metrics

Metric	Value	Notes
Total Sessions	16	34 sessions skipped (no logs)
Successful Completions	6 (37.5%)	✅
Failed/Abandoned	0 (0%)	✅
Unknown Status	10 (62.5%)	⚠️ Mostly skipped sessions
Average Duration (All)	58.5 min	⚠️ Inflated by skipped sessions
Average Duration (Success)	6.5 min	✅ Efficient
Loop Detection Rate	2 (12.5%)	✅ Low
Context Issues	6 (37.5%)	⚠️ Moderate

Success Factors ✅

Patterns associated with successful task completion:

1. Efficient Tool Usage

• Success rate: 100% for sessions with 150+ tool calls
• Example: "Addressing comment on PR Add "Use Shared Agentic Workflows" subsection to create.md #13686" - 169 tools in 8.9 min
• Example: "Security Guard Agent 🛡️" - 1008 tools in 4.1 min (exceptional efficiency)

2. Clear Task Context

• Success rate: 66.7% when task name is descriptive
• Example: "Addressing comment on PR Add "Use Shared Agentic Workflows" subsection to create.md #13686" provides specific context
• Sessions with clear objectives completed faster (avg 6.5 min)

3. Minimal Loop Patterns

• 66.7% of successful sessions had zero loops
• Only 1 successful session had loops (Security Guard Agent with 7 loops but still succeeded)
• Low loop count correlates with faster completion

Failure Signals ⚠️

Common indicators of inefficiency or unclear outcomes:

1. Session Skipping

• Issue: 62.5% of sessions had "unknown" status (skipped, no logs generated)
• Impact: Unable to determine what happened or why they were skipped
• Examples: Scout, Q, Archie, PR Nitpick Reviewer (all skipped)

2. Error Presence in Logs

• 6 sessions (37.5%) had errors in logs, but all still succeeded
• Suggests errors may be warnings or non-critical issues
• Need better classification of error severity

3. Variable Duration

• Unknown status sessions show 89+ minute durations (likely timeout/skip)
• Creates misleading metrics when aggregated
• Recommendation: Filter or separate skipped sessions in analysis

Prompt Quality Analysis 📝

Assessment Methodology

Based on heuristics:

• High Quality: Descriptive name (>20 chars), no errors, duration <10 min
• Medium Quality: Moderate clarity, some issues
• Low Quality: Vague names (<10 chars), errors, or long duration (>30 min)

Current Distribution

• High-Quality Prompts: 0 (0%)
• Medium-Quality Prompts: 0 (0%)
• Low-Quality Prompts: 16 (100%) ⚠️

Analysis

The prompt quality assessment may be too strict. Successful sessions like "Addressing comment on PR #13686" (31 chars) had errors in logs but completed efficiently. The current heuristic needs refinement.

Observed Patterns in Successful Sessions

What Worked:

✅ "Addressing comment on PR #13686"
   - Specific PR reference
   - Clear action ("Addressing comment")
   - Context provided

✅ "Security Guard Agent 🛡️"
   - Role-specific agent name
   - High tool usage suggests thorough analysis
```

**Skipped Sessions** (Unable to analyze):
```
❌ "Scout" - Skipped, no logs
❌ "Q" - Skipped, no logs
❌ "/cloclo" - Skipped, no logs
```

## Notable Observations

### Loop Detection
- **Sessions with loops**: 2 (12.5%)
- **Average loop count**: 3.5 (among sessions with loops)
- **Notable**: Security Guard Agent had 7 loops but still succeeded in 4.1 minutes
- **Insight**: Loops don't always indicate failure - may represent iterative refinement

### Tool Usage
- **Most efficient**: Security Guard Agent - 1008 tools in 4.1 min (246 tools/min)
- **Typical range**: 169-187 tools for PR comment resolution
- **Correlation**: Higher tool usage correlates with task complexity, not failure

### Context Issues
- **Sessions with errors**: 6 (37.5%), but all succeeded
- **Interpretation**: "Errors" in logs may include warnings or expected failures
- **Recommendation**: Implement error severity classification

### Temporal Patterns (Experimental Analysis)

**Hour-of-Day Analysis**:
- **Peak activity**: 8:00-10:00 UTC (8-10 AM)
- **8 AM**: 10 sessions (7 skipped)
- **10 AM**: 6 sessions (3 successful)
- **Finding**: Morning hours (8-10 AM UTC) see highest activity
- **Success rates**: Similar across analyzed hours (~50% excluding skipped)

## Experimental Analysis

**This run included experimental strategy**: Temporal Analysis

### Approach
Analyzed session timing patterns to identify:
1. Hour-of-day effects on session success
2. Duration trends by time of day
3. Tool usage patterns correlated with timing

### Findings

**1. Session Clustering**
   - Sessions cluster around 8-10 AM UTC
   - Suggests batch processing or scheduled triggers
   - May indicate PR review workflow timing

**2. Duration Patterns**
   - Successful sessions consistently short (4-9 minutes)
   - Skipped sessions show uniform 89-90 minute duration (timeout threshold?)
   - No significant hour-of-day effect on successful session duration

**3. Tool Usage Consistency**
   - Tool usage independent of time of day
   - Determined by task complexity, not timing
   - Security agents use 5-6x more tools than PR comment tasks

### Effectiveness
**Rating**: Medium

**Insights Gained**:
- Identified session clustering patterns
- Revealed potential timeout threshold (90 minutes)
- Confirmed task complexity drives tool usage, not timing

**Limitations**:
- Only one day of data limits temporal trend analysis
- Most sessions skipped, reducing sample size
- Need multi-day analysis for true temporal patterns

**Recommendation**: **Refine** - Continue temporal analysis with larger dataset

## Actionable Recommendations

### For Users Writing Task Descriptions

#### 1. **Provide Specific Context**
   - ❌ Avoid: "Fix the code"
   - ✅ Better: "Addressing comment on PR #13686 - refactor error handling"
   - **Impact**: High - Specific context correlates with 66.7% success rate

#### 2. **Reference Concrete Artifacts**
   - Include PR numbers, issue IDs, file paths when relevant
   - Example: "PR #13686" provides clear scope
   - **Impact**: High - Helps agent locate relevant context quickly

#### 3. **Set Clear Objectives**
   - State the expected outcome
   - Example: "Add error handling to API client" vs. "Improve code"
   - **Impact**: Medium - Helps agent validate completion

### For System Improvements

#### 1. **Session Skipping Analysis**
   - **Issue**: 62.5% of sessions skipped with no logs
   - **Recommendation**: Investigate why sessions are skipped
   - **Potential causes**: Duplicate triggers, dependency failures, filter rules
   - **Impact**: High - Understanding skip patterns improves reliability

#### 2. **Error Severity Classification**
   - **Issue**: All sessions with "errors" still succeeded
   - **Recommendation**: Classify errors by severity (warning, error, critical)
   - **Benefit**: More accurate failure prediction and diagnostics
   - **Impact**: Medium - Improves metrics accuracy

#### 3. **Timeout Threshold Review**
   - **Observation**: Skipped sessions show 89-90 minute duration
   - **Recommendation**: Review timeout settings and skip logic
   - **Consider**: Dynamic timeouts based on task complexity
   - **Impact**: Low - May reduce false timeouts

### For Tool Development

#### 1. **Session Logging Enhancement**
   - **Need**: Better visibility into skipped sessions
   - **Recommendation**: Log skip reasons and metadata
   - **Frequency**: 34 sessions skipped today
   - **Use case**: Debugging workflow configuration issues
   - **Impact**: High - Essential for understanding skips

#### 2. **Loop Detection Refinement**
   - **Need**: Distinguish productive loops from stuck patterns
   - **Current**: Simple repetition counting
   - **Recommendation**: Analyze loop purpose (refinement vs. stuck)
   - **Example**: Security Guard Agent's 7 loops were productive
   - **Impact**: Medium - Better efficiency metrics

#### 3. **Tool Usage Metrics Dashboard**
   - **Need**: Real-time visibility into tool usage patterns
   - **Value**: Identify unusually high/low tool usage
   - **Example**: 1008 tools in 4.1 min is exceptional but not flagged
   - **Impact**: Low - Nice to have for monitoring

## Trends Over Time

**Historical Context**: This is the first analysis run with the new temporal analysis strategy.

**Baseline Established**:
- Completion rate: 37.5% (16 sessions)
- Average successful duration: 6.5 minutes
- Loop rate: 12.5%
- Error presence: 37.5% (but doesn't prevent success)

**Future Tracking**:
- Monitor completion rate trends
- Track duration efficiency improvements
- Observe skip rate changes
- Correlate with system changes

## Statistical Summary

```
Total Sessions Analyzed:     16
Successful Completions:      6 (37.5%)
Failed Sessions:            0 (0%)
Abandoned Sessions:         0 (0%)
Unknown Status:            10 (62.5%)

Average Session Duration:   58.5 min (overall)
  Successful Sessions:       6.5 min
  Unknown/Skipped:          89.2 min
Median Session Duration:    89.2 min
Longest Session:           90.2 min
Shortest Session:           3.7 min

Loop Detection:             2 sessions (12.5%)
  Average loops:            3.5 (when present)
  Max loops:                7 (Security Guard Agent)

Context Issues:             6 sessions (37.5%)
Tool Failures:              0 occurrences

High-Quality Prompts:       0 (0%) ⚠️
Medium-Quality Prompts:     0 (0%) ⚠️
Low-Quality Prompts:       16 (100%) ⚠️
  (Note: Heuristic needs refinement)

Key Insights Summary

What's Working Well ✅

1. Efficiency: Successful sessions complete in 4-9 minutes
2. Tool utilization: Agents use tools effectively (169-1008 calls)
3. Low loop rate: Only 12.5% of sessions have loops
4. Zero hard failures: No failed status recorded

Areas for Investigation ⚠️

1. High skip rate: 62.5% of sessions skipped without logs
2. Prompt quality metrics: Current heuristic too strict (100% "low quality")
3. Error classification: Need severity levels for better diagnostics
4. Timeout behavior: 90-minute duration suggests timeout threshold

Experimental Findings 🔬

1. Session clustering: Activity peaks at 8-10 AM UTC
2. Tool usage independence: Time of day doesn't affect tool usage
3. Consistency: Successful sessions consistently efficient regardless of timing

Next Steps

• Analyze 16 Copilot agent sessions
• Apply temporal analysis experimental strategy
• Identify success and failure patterns
• Generate actionable recommendations
• Investigate high session skip rate (Priority: High)
• Refine prompt quality heuristic (Priority: Medium)
• Implement error severity classification (Priority: Medium)
• Schedule follow-up analysis in 7 days
• Collect multi-day data for temporal trend validation

---

Analysis generated automatically on 2026-02-04 at 13:38 UTC
Experimental Strategy: Temporal Analysis
Sessions: 16 analyzed, 34 skipped (50 total fetched)

AI generated by Copilot Session Insights

• expires on Feb 11, 2026, 1:42 PM UTC

[github-actions[bot]]

This discussion was automatically closed because it expired on 2026-02-11T13:42:48.001Z.

Closed by Workflow