-
Notifications
You must be signed in to change notification settings - Fork 47
Closed as not planned
Closed as not planned
Copy link
Labels
automationcode-qualitycookieIssue Monster Loves Cookies!Issue Monster Loves Cookies!critical-priorityinvestigationtask-mining
Description
Description
Analysis of 4,389 copilot agent tasks shows a concerning decline in success rates during January 2026. Success rate dropped from 76.2% in November 2025 to 64.8% in January 2026 - an 11.4 percentage point decrease.
Trend Data
| Month | Tasks | Success Rate | Change |
|---|---|---|---|
| Oct 2025 | 397 | 73.3% | baseline |
| Nov 2025 | 884 | 76.2% | +2.9% ✅ |
| Dec 2025 | 1,348 | 71.6% | -4.6% |
| Jan 2026 | 1,760 | 64.8% | -11.4% 🚨 |
Impact
- ~200 additional failed tasks in January compared to November baseline
- Consistent downward trend since November peak
- Affects all task types - not isolated to one category
Investigation Areas
1. Recent Agent Instruction Changes
- Review changes to agent prompts in December-January
- Check for new constraints or guidelines that may be too restrictive
- Analyze prompt length and complexity trends
2. Infrastructure Changes
- Check for GitHub Actions runner updates
- Review MCP server availability and performance
- Analyze network/timeout issues
3. Task Complexity Increase
- Compare average files changed per task over time
- Analyze commit count trends
- Review task description length and clarity
4. Tooling Changes
- Check for linter/formatter updates
- Review dependency version changes
- Analyze tool availability issues
Proposed Investigation Steps
-
Data Analysis (Day 1)
- Pull detailed metrics for Nov 2025 vs Jan 2026
- Compare task types, complexity, and failure patterns
- Identify specific failure categories driving the decline
-
Code Review (Day 2)
- Review commits between Nov-Jan affecting agent behavior
- Check for prompt changes, validation changes, tool updates
- Identify configuration changes
-
Root Cause Analysis (Day 3)
- Correlate changes with success rate drops
- Test hypothesis with sample task replays
- Document findings with evidence
-
Remediation Plan (Day 3)
- Propose specific fixes based on root cause
- Prioritize by impact
- Create follow-up issues for implementation
Success Criteria
- Root cause(s) identified with supporting data
- Correlation between changes and success rate decline established
- Remediation plan with specific action items created
- Follow-up issues created for each fix
- Success rate returns to >70% baseline within 2 weeks of fixes
Priority
Critical - 11.4% decline affects hundreds of tasks and project velocity
Source
Extracted from Copilot Agent Prompt Clustering Analysis - January 2026
Estimated Effort
3-5 days - Requires comprehensive investigation across multiple areas
Data Sources
- Discussion [prompt-clustering] 🔬 Copilot Agent Prompt Clustering Analysis - January 2026 #12473 - Prompt clustering analysis with temporal trends
- Session logs from Nov 2025 - Jan 2026
- GitHub Actions workflow run history
- Agent prompt version history
Follow-up Required
This is an investigation task that will likely spawn multiple implementation tasks once root causes are identified.
AI generated by Discussion Task Miner - Code Quality Improvement Agent
- expires on Feb 12, 2026, 9:15 AM UTC
Reactions are currently unavailable
Metadata
Metadata
Assignees
Labels
automationcode-qualitycookieIssue Monster Loves Cookies!Issue Monster Loves Cookies!critical-priorityinvestigationtask-mining