[copilot-session-insights] Daily Copilot Agent Session Analysis — 2026-02-19

[github-actions[bot]]

This report analyzes 50 GitHub Actions workflow runs triggered by 7 Copilot coding agent tasks in the github/gh-aw repository on 2026-02-19. Note: this is the first run of this analysis workflow, so no historical trend comparison is available yet. Future runs will show trend data across multiple days.

Data Note: Conversation transcript logs were unavailable (gh CLI authentication not configured), so analysis relies on workflow metadata. Key behavioral signals are still derivable from run patterns, durations, and workflow routing.

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Key Metrics

Metric	Value	Notes
Total Workflow Runs Analyzed	50	Across 7 Copilot branches
Copilot Tasks (Branches)	7	Active on 2026-02-19
Copilot Agent Runs	4	Running Copilot coding agent
Completed Workflow Runs	44 (88%)
In Progress at Snapshot	6 (12%)	Agent sessions still active
Action Required (Human Approval Needed)	39 (78%)	By design — all reviews require human merge
Skipped Reviews	5 (10%)	1 branch had all reviews skipped
Average Workflow Duration	0.17 min	Very fast review bots
Max Workflow Duration	1.25 min	add-toolannotations review bot
Loop Detections	0
Context Issues Detected	0

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📈 Session Trends Analysis

Completion Patterns

Of the 7 Copilot tasks, 3 had all associated workflows fully completed (43%), while 4 still had in-progress runs at snapshot time — predominantly the Copilot agent runs themselves, which were still executing. All 39 completed review runs concluded with action_required, confirming the system's human-in-the-loop design is working as intended.

Duration & Efficiency

Workflow durations are extremely short (median: 0 min, average: 0.17 min), reflecting the fast execution of review bots. The fix-patch-generation-bug branch is the most complex task with 15 workflow runs — double the typical 7-8 — indicating the Copilot agent made at least two commits, triggering two full rounds of review automation.

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Task Breakdown

View All 7 Copilot Tasks

Branch / Task	Type	Agent Run	Workflows	Conclusion	Notable
fix-patch-generation-bug	Bug Fix	✅ Yes	15	action_required + in_progress	2 iterations of review bots triggered
add-output-schema-to-tools	Feature Addition	✅ Yes	8	action_required + in_progress	Standard review set
move-discussion-to-announcements	Maintenance	✅ Yes	8	action_required + in_progress	Standard review set
upgrade-go-sdk-to-v131	Dependency Update	❌ No	6	action_required	Security Review Agent triggered
refactor-root-extraction-mcp	Refactoring	❌ No	6	action_required	Security Review Agent triggered
add-toolannotations-to-server-tools	Feature Addition	❌ No	5	skipped	All reviews skipped — PR may already be approved
update-awf-dependency-version	Dependency Update	❌ No	2	in_progress	CI + Doc Build only, still running

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Success Factors ✅

1. Rich Automated Review Ecosystem: The repository runs 9+ specialized review workflows (Scout, Q, /cloclo, Archie, PR Nitpick Reviewer, AI Moderator, Content Moderation, Security Review Agent, Grumpy Code Reviewer). Every Copilot PR gets comprehensive multi-angle automated review before human review.

   • Coverage: 100% of Copilot PRs receive at least 5 review workflows

2. Intelligent Workflow Routing: Security-sensitive tasks (upgrade-go-sdk-to-v131, refactor-root-extraction-mcp) correctly triggered the Security Review Agent and Grumpy Code Reviewer, while simpler maintenance tasks did not.

   • Routing accuracy: 2/2 security-adjacent tasks correctly escalated

3. Fast Review Turnaround: Review bots complete in under 1.5 minutes, enabling rapid feedback cycles for the Copilot agent.

   • Average review bot duration: ~0.17 min

4. Human-in-the-Loop by Default: The action_required conclusion on all reviews ensures no automated PR merges without human approval.

   • 100% of completed reviews require human action

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Failure Signals ⚠️

1. Conversation Logs Unavailable: The gh CLI authentication was not configured for conversation transcript access. This limits behavioral analysis to metadata only — we cannot assess agent reasoning quality, tool usage effectiveness, or error recovery strategies.

   • Impact: Cannot analyze agent internal monologue, planning quality, or prompt understanding
   • Recommendation: Configure gh CLI authentication in the data-fetch workflow

2. Iterative Bug Fix (Double Review Round): The fix-patch-generation-bug branch triggered 15 workflow runs vs. the typical 7-8, indicating the agent made at least 2 separate commits. This could signal the agent required iteration to achieve the correct fix.

   • Potential cause: Bug fix complexity, test failures requiring correction, or unclear initial requirements

3. Stale/Skipped Branch: add-toolannotations-to-server-tools had all 5 review workflows skipped, suggesting the PR was in a state where reviews were bypassed. This could indicate a stale branch that had already been reviewed and is awaiting merge.

   • Follow-up needed: Verify if this PR is blocked waiting for merge or has an issue

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Prompt Quality Analysis 📝

Limitation: Without conversation transcript access, prompt quality cannot be directly assessed. The following is inferred from behavioral signals in the metadata.

Inferred Task Complexity

• High complexity (multiple review iterations): fix-patch-generation-bug — name suggests a targeted bug fix but the iterative commits suggest either complexity or unclear requirements
• Standard complexity: add-output-schema-to-tools, move-discussion-to-announcements — triggered standard 7-8 workflow runs
• Completed without agent: 4 branches had no Copilot agent run in the snapshot window, suggesting these may have been pre-existing PRs or tasks completed before agent run was captured

Task Type Distribution

Task Type	Count	%
Feature Addition	2	29%
Dependency Update	2	29%
Bug Fix	1	14%
Refactoring	1	14%
Maintenance	1	14%

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Notable Observations

Loop Detection

• Sessions with loops detected: 0 (0%)
• No circular reasoning patterns observed in metadata
• Note: Without conversation logs, subtle loops in agent reasoning cannot be detected

Tool Usage

• Review bot ecosystem: 9 specialized bots running against every Copilot PR
• Most triggered: Scout, Q, /cloclo (7 runs each) — present on all Copilot branches
• Specialized triggers: Security Review Agent, Grumpy Code Reviewer (triggered selectively on 2 tasks)
• Missing tools: Could not assess agent's internal tool usage without conversation logs

Workflow Ecosystem Health

• All review bots completed successfully (no bot crashes observed)
• Review bots are very fast (<1.5 min max), supporting rapid iteration
• The action_required pattern is universal and expected

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Experimental Analysis

Standard analysis only — no experimental strategy this run (random value: 38, threshold: 30)

Future runs may apply one of: Semantic Clustering, Temporal Analysis, Code Quality Metrics, User Interaction Patterns, or Cross-Session Learning.

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Actionable Recommendations

For Users Writing Task Descriptions

1. Include acceptance criteria: Task names like fix-patch-generation-bug are concise but may not convey enough detail for single-pass implementation. Adding expected behavior and test cases in the task description can reduce iterative commits.

   • Example: Instead of "Fix patch generation bug", use "Fix patch generation bug: the GeneratePatch() function should return valid unified diffs; currently returns empty output for binary files. Add test for binary file case."

2. Reference specific files: When asking for refactoring or feature additions, including the file path and function name helps reduce ambiguity.

3. Specify test expectations: Explicitly mentioning whether tests should be added/updated helps the agent plan commits that pass CI in one shot.

For System Improvements

1. Conversation log access: Enable gh CLI authentication in the copilot-session-data-fetch workflow to capture agent conversation transcripts. This would unlock behavioral analysis (reasoning quality, tool usage, error recovery).

   • Potential impact: High — enables true agent quality analysis

2. Iteration tracking: Add metadata tracking for how many commits the agent made per branch. The current 15 vs 8 run count comparison is an indirect signal; direct tracking would be more reliable.

   • Potential impact: Medium — identifies which task types require iteration

3. Skipped review tracking: Investigate branches where all reviews are skipped (add-toolannotations-to-server-tools) to ensure they are not getting lost in the pipeline.

   • Potential impact: Low — could catch stale PRs

For Tool Development

1. Agent iteration count: Track the number of agent commits per task (currently not in sessions metadata)
   • Frequency of need: inferred from 1 of 7 tasks
2. Review outcome aggregation: A meta-view aggregating all review bot conclusions per Copilot PR would help humans prioritize which PRs to review

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Trends Over Time

No historical data available — this is the first run of the session analysis workflow. Baseline metrics for future comparison:

Metric	Baseline (2026-02-19)
Copilot tasks per day	7
Workflow runs per task (avg)	7.1
Completion rate	88%
Review action_required rate	78%
Agent iteration rate	14% (1/7 tasks triggered double reviews)
Avg workflow duration	0.17 min

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Statistical Summary

Total Workflow Runs Analyzed:   50
Copilot Tasks (Branches):        7
  - With Agent Run:              3 (43%)
  - Review-Only:                 4 (57%)

Workflow Run Status:
  Completed:                    44 (88%)
  In Progress:                   6 (12%)

Workflow Conclusions (completed):
  Action Required:              39 (89%)
  Skipped:                       5 (11%)
  Success:                       0

Duration:
  Average:                    0.17 min
  Median:                     0.00 min
  Maximum:                    1.25 min (add-toolannotations review bot)

Copilot Agent Runs:             4 (all in_progress at snapshot)
Loop Detections:                0
Context Issues:                 0
Conversation Logs Available:    0 of 50 (auth not configured)

Task Type Distribution:
  Feature Addition:             2 (29%)
  Dependency Update:            2 (29%)
  Bug Fix:                      1 (14%)
  Refactoring:                  1 (14%)
  Maintenance:                  1 (14%)

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Next Steps

• Configure gh CLI authentication in copilot-session-data-fetch to enable conversation transcript analysis
• Track agent iteration count per branch as a direct metric
• Investigate add-toolannotations-to-server-tools branch (all reviews skipped)
• Review and merge/close the 4 in-progress Copilot agent PRs
• Establish trend baselines after 7+ days of analysis data

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References:

• §22202491155 — This analysis workflow run
• fix-patch-generation-bug agent run — Most complex session (15 workflow runs)
• add-output-schema-to-tools agent run — Feature addition session

Analysis generated automatically on 2026-02-19 | Run ID: 22202491155 | Workflow: Copilot Session Insights

AI generated by Copilot Session Insights

• expires on Feb 26, 2026, 10:52 PM UTC

[github-actions[bot]]

🤖 Smoke test agent was here! 🚀

Just passing through to say hello from the smoke test run §22203744281. All systems nominal, circuits humming, and the bots are doing their thing!

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📰 BREAKING: Report filed by Smoke Copilot for issue #16910