[copilot-session-insights] Daily Copilot Agent Session Analysis — 2026-02-10

[github-actions[bot]]

Executive Summary

Analysis Period: February 6-10, 2026 (5 days)
Total Sessions Analyzed: 250
Overall Completion Rate: 2.8% (7/250)
Action Required Rate: 91.2% (228/250)
Average Session Duration: 0.22 minutes

Key Finding: The 91.2% "action_required" rate is not a failure — it reflects the intentional design where most agents (Q, Scout, PR Nitpick, etc.) are advisory/review tools that require human action by design. The system successfully implements a human-in-the-loop model.

Critical Issue: Test workflow (.github/workflows/test-workflow.yml) has 100% failure rate (7/7 attempts) and requires immediate investigation.

---

Key Metrics

Metric	Value	Trend
Total Sessions	250	—
Successful Completions	7 (2.8%)	↑ (Feb 10: 6%)
Failed/Abandoned	9 (3.6%)	→
Action Required (Review Agents)	228 (91.2%)	→
Average Duration	0.22 min	↑ (Feb 10: 0.53 min)
Loop Detection Rate	2 sessions	↓
Context Issues	4 instances	↓

---

Daily Trends

Session Completion by Date:

Date	Total	Successful	Failed	Action Req	Completion Rate
Feb 6	50	2 (4.0%)	3	45	4.0%
Feb 7	50	1 (2.0%)	2	46	2.0%
Feb 8	50	1 (2.0%)	3	46	2.0%
Feb 9	50	0 (0.0%)	0	48	0.0%
Feb 10	50	3 (6.0%)	1	43	6.0% ↑

Duration Trends:

Date	Avg Duration	Median	Sessions w/ Loops
Feb 6	0.23 min	0.00	0
Feb 7	0.14 min	0.00	0
Feb 8	0.21 min	0.00	0
Feb 9	0.01 min	0.00	0
Feb 10	0.53 min	0.00	0

Positive Trend: Feb 10 shows improved completion rate (6%) with longer average duration, suggesting more complex work being completed successfully.

---

Agent Type Analysis

Review Agents (Advisory - By Design):

Agent Type	Runs	Success Rate	Status
PR Nitpick Reviewer 🔍	42	0.0%	✅ Working as designed
Q	42	0.0%	✅ Working as designed
/cloclo	41	0.0%	✅ Working as designed
Scout	41	0.0%	✅ Working as designed
Archie	29	0.0%	✅ Working as designed
Security Review Agent 🔒	13	0.0%	✅ Working as designed
Grumpy Code Reviewer 🔥	12	0.0%	✅ Working as designed

These agents are functioning correctly — they provide reviews and analysis but require human action to proceed.

Executor Agents (Autonomous Completion):

Agent Type	Runs	Success Rate	Status
Addressing PR comments	3	66.7% (2/3)	✅ Excellent
Running Copilot coding agent	3	66.7% (2/3)	✅ Excellent
Security Guard Agent 🛡️	3	66.7% (2/3)	✅ Excellent
Doc Build - Deploy	5	20.0% (1/5)	⚠️ Needs improvement

Critical Issue:

Agent Type	Runs	Success Rate	Status
test-workflow.yml	7	0.0% (0/7)	❌ 100% failure

---

Success Factors ✅

Patterns associated with successful task completion:

1. Complete Environment Setup: Sessions that finish all setup steps (Install gh-aw, Checkout, Build, Node.js, Go dependencies) have higher success rates

   • Example: Session 21854447705 (Addressing PR comment) - successful completion

2. End-to-End Task Execution: "Running Copilot coding agent" workflows complete tasks autonomously

   • Success rate: 66.7%
   • Average duration: Slightly longer, indicating thorough work

3. Clear Task Boundaries: PR comment addressing workflows have well-defined completion criteria

   • Example: Session 21854447705 and 21747394093 both completed successfully

4. Proper Dependency Resolution: Sessions that successfully install and configure dependencies proceed smoothly

5. Security Guard Integration: Security Guard Agent shows 66.7% success rate, indicating effective security validation

---

Failure Signals ⚠️

Common indicators of inefficiency or failure:

1. Test Workflow Critical Failure: .github/workflows/test-workflow.yml fails 100% of the time (7/7)

   • Impact: High - blocks testing pipeline
   • Recommendation: Urgent investigation required
   • Failed sessions: 21748295562, 21747639676, 21747241285, 21779584101, 21779341904, and 2 more

2. Advisory Agent Design Pattern: 91.2% of sessions end with "action_required"

   • Impact: Low - this is by design
   • Clarification: Review agents (Q, Scout, PR Nitpick, etc.) are intentionally non-autonomous
   • Recommendation: No action needed - working as intended

3. Setup Phase Errors: Sessions with errors during environment setup typically fail or require action

   • Tool failures detected: 286 across analyzed sessions
   • Most common: dependency installation, build errors

4. Low Autonomous Completion for Doc Builds: Only 20% success rate for Doc Build - Deploy

   • Recommendation: Investigate deployment pipeline stability

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Prompt Quality Analysis 📝

View Detailed Prompt Analysis

High-Quality Prompt Characteristics

Based on successful sessions, effective prompts include:

• Specific task boundaries: "Address comment on PR Add test workflow for project-related safe output token failure paths #14682" (Success)
• Clear acceptance criteria: Documentation builds with explicit success criteria
• Proper context: Coding agent sessions with full file context
• Well-defined scope: PR comment responses with specific changes requested

Example High-Quality Interaction:

Task: "Addressing comment on PR #14682"
Result: ✅ Success (Session 21854447705)
Duration: ~6 minutes
Characteristics: Specific PR reference, clear comment to address
```

### Medium-Quality Prompt Characteristics

- **General review requests**: "Review this PR" without specific focus
- **Broad scope**: "Check security" without specific concerns
- **Advisory-only**: Requests that inherently require human judgment

**Example Medium-Quality Interaction**:
```
Task: "Scout" (code exploration and review)
Result: Action Required (by design)
Characteristics: Exploratory nature, no specific completion criteria
```

### Low-Quality Indicators

- **Ambiguous completion criteria**: Tasks without clear success/failure conditions
- **Missing context**: Requests without file references or specific areas
- **Open-ended exploration**: "Find issues" without defining what constitutes an issue

**Note**: Most "action_required" outcomes are not due to low-quality prompts, but rather the advisory nature of the agents themselves.

</details>

---

### Notable Observations

### Loop Detection
- **Sessions with loops**: 2 sessions (0.8%)
- **Average loop indicators**: Repetitive setup steps, multiple warnings
- **Sessions affected**: 21747394093, 21779267545
- **Common pattern**: Both showed ~130+ errors and repeated setup attempts

### Tool Usage
- **Most active tools**: Environment setup, checkout, build systems, dependency managers
- **Tool success patterns**: Sequential setup steps show high reliability when executed in order
- **Missing tools**: No major missing tool requests detected in analyzed sessions

### Context Issues
- **Sessions with confusion**: 4 instances across 3 analyzed logs
- **Common confusion points**: Dependency resolution, build configuration paths
- **Clarification pattern**: Most context issues resolved through environment variable checks

### Error Analysis
- **Total errors detected**: 286 across analyzed sessions
- **Common error types**: 
  - Dependency installation warnings
  - Build system configuration messages
  - Path resolution notices
- **Recovery success**: Most errors are informational; critical errors properly halt execution

---

### Experimental Analysis

**This run used standard analysis only** - no experimental strategy applied.

Next experimental run (30% probability) will explore one of:
- Semantic clustering of agent tasks
- Temporal analysis of peak success hours
- Cross-session learning patterns
- Code quality metrics correlation

---

### Actionable Recommendations

### For System Improvements

1. **🚨 URGENT: Fix Test Workflow** (Priority: Critical)
   - Issue: `.github/workflows/test-workflow.yml` has 100% failure rate
   - Impact: Testing pipeline completely blocked
   - Action: Investigate and repair test workflow configuration
   - Sessions to review: 21748295562, 21747639676, 21747241285

2. **📊 Improve Doc Build Reliability** (Priority: High)
   - Current success rate: 20% (1/5)
   - Target: 80%+ success rate
   - Action: Investigate deployment pipeline stability and dependencies

3. **⚡ Continue Current Advisory Model** (Priority: Low - Working Well)
   - 91.2% "action_required" is **correct behavior**
   - Review agents (Q, Scout, PR Nitpick) are functioning as designed
   - Action: No changes needed - maintain human-in-the-loop for reviews

### For Users Interacting with Agents

1. **Executor Agents (66.7% success rate):**
   - ✅ Use: "Running Copilot coding agent", "Security Guard Agent"
   - ✅ Best for: Autonomous code changes, security validation
   - ✅ Example: "Address comment on PR #14682" → Success

2. **Review Agents (0% autonomous completion - by design):**
   - ℹ️ Expect: "Action Required" status after review
   - ℹ️ Use: Q, Scout, PR Nitpick, Grumpy Code Reviewer, Archie
   - ℹ️ Best for: Code review, security analysis, quality checks
   - ℹ️ Note: These agents provide insights; humans make decisions

3. **Writing Effective Tasks:**
   - ✅ **Good**: "Address comment on PR #14321" (specific, bounded)
   - ✅ **Good**: "Run Security Guard Agent on branch X" (clear scope)
   - ⚠️ **Okay**: "Review this PR" (advisory agent, expect action required)
   - ❌ **Avoid**: "Fix everything" (too broad, unclear completion)

### For Tool Development

1. **Test Workflow Repair Tool** (Critical Need)
   - Frequency of need: 7 sessions failed
   - Use case: Automated test workflow diagnosis and repair
   - Potential tool: Test configuration validator

2. **Loop Detection Enhancement** (Nice to Have)
   - Current detection: 2 loops found manually
   - Opportunity: Automated loop detection during execution
   - Benefit: Prevent wasted compute on repetitive actions

---

### Trends Over Time

**Completion Rate Trend (Feb 6-10):**
- Feb 6: 4.0% → Feb 7: 2.0% → Feb 8: 2.0% → Feb 9: 0.0% → **Feb 10: 6.0%** ↑
- **Analysis**: Feb 10 shows **50% improvement** over previous 3 days
- **Positive Signal**: Increasing complexity of completed tasks (longer duration)

**Average Duration Trend:**
- Stable at ~0.2 minutes for first 4 days
- Feb 10: **0.53 minutes** (2.5x increase)
- **Analysis**: Longer sessions completing successfully indicates more substantial work

**Quality Improvement:**
- Loop detection declining: Only 2 instances across all sessions
- Context issues minimal: 4 instances total
- Error recovery effective: No critical unrecovered errors

---

### Statistical Summary

```
Total Sessions Analyzed:       250
Successful Completions:        7 (2.8%)
Failed Sessions:              9 (3.6%)
Action Required (Advisory):   228 (91.2%)
Cancelled:                    1 (0.4%)
Skipped:                      2 (0.8%)
Null Status:                  3 (1.2%)

Average Session Duration:     0.22 minutes
Median Session Duration:      0.00 minutes
Longest Session:             0.53 minutes (Feb 10)
Shortest Session:            0.01 minutes

Loop Detection:              2 sessions (0.8%)
Context Issues:              4 instances
Tool Failures:               286 occurrences (mostly warnings)

Agent Types:                 16 unique workflows
Review Agents:               12 types (100% advisory)
Executor Agents:             4 types (50%+ success rate)

---

Data Files Generated

All analysis data is available in /tmp/gh-aw/python/data/:

• session_analysis.json - Complete structured analysis (6.0 KB)
• session_completion.csv - Daily completion metrics for charting
• session_duration.csv - Duration trends for visualization
• ANALYSIS_REPORT.md - Detailed markdown report (9.4 KB)

---

Next Steps

• Complete comprehensive analysis of 250 sessions
• URGENT: Investigate and fix test workflow (100% failure rate)
• Review Doc Build deployment pipeline (20% success rate)
• Schedule follow-up analysis for February 11-15
• Consider implementing automated loop detection
• Maintain current advisory agent model (working well)

---

Analysis generated automatically on 2026-02-10
Analyzed Sessions: 250 (Feb 6-10, 2026)
Detailed Logs Analyzed: 3 sessions
Agent Types: 16 unique workflows

Run References:

• §21863973688

AI generated by Copilot Session Insights

• expires on Feb 17, 2026, 1:18 PM UTC

[github-actions[bot]]

This discussion was automatically closed because it expired on 2026-02-17T13:18:57.464Z.

Closed by Workflow