dss/.dss/CHALLENGE_CROSS_REALITY_AUDIT.md

ZEN CHALLENGE: Cross-Reality Design System Audit

A Multi-Agent Collaboration Challenge for DSS PowerTools

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Challenge Overview

Difficulty: EXPERT

Agents Required: 5 (Architect, Local Scout, Staging Inspector, Production Monitor, Synthesizer)

Estimated Duration: 4-6 hours

Objective: Perform a comprehensive design system audit across three runtime environments (local, staging, production) using adaptive LOCAL/REMOTE modes, then synthesize findings into an actionable improvement plan.

Prerequisites:

• DSS PowerTools plugin installed
• Access to local development environment
• Access to staging.dss.overbits.luz.uy (REMOTE)
• Access to dss.overbits.luz.uy (REMOTE)
• Task queue MCP server running
• Browser-logger.js active on both remote environments

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Challenge Scenario

Your design system team needs to understand the current state of design token adoption, component consistency, and runtime health across all environments. A previous audit was done 3 months ago, but the system has evolved significantly. You need a fresh, comprehensive analysis.

Business Context:

• 47 React components in the library
• 6 teams consuming the design system
• Recent reports of "visual inconsistencies" between environments
• Performance concerns on production
• Need data-driven prioritization for Q1 improvements

Technical Context:

• Design tokens defined in tokens/ directory
• Components in components/ directory
• Storybook for visual testing
• Multiple deployment environments
• Browser logs captured via auto-sync system

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Agent Roles & Responsibilities

Agent 1: ARCHITECT (Planning & Coordination)

Mode: N/A (coordination only)

Responsibilities:

1. Design the audit strategy
2. Define success criteria
3. Create audit checklist
4. Coordinate other agents via task-queue
5. Monitor overall progress

Tools Available:

• /dss-status - Check mode capabilities
• Task queue for agent coordination
• Planning skills

Deliverables:

• Audit strategy document
• Success criteria checklist
• Agent task assignments
• Coordination plan

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Agent 2: LOCAL SCOUT (Local Development Audit)

Mode: LOCAL

Environment: Developer's local machine

Responsibilities:

1. Audit local component library
2. Extract design tokens from source
3. Capture Storybook screenshots
4. Check for hardcoded values
5. Analyze component adoption patterns

Tools Available:

• /dss-config set local - Switch to LOCAL mode
• /dss-audit components/ - Component audit
• /dss-extract src/ --tokens - Token extraction
• /dss-screenshot Button --story all - Capture screenshots
• /dss-analyze components/ - Pattern analysis
• Direct filesystem access via LOCAL strategy

Deliverables:

• Component audit report (hardcoded values, token usage)
• Extracted token inventory
• Screenshot collection from Storybook
• Local console logs
• Filesystem scan results

Session Data to Share:

• Local token inventory (JSON)
• Screenshot URLs/paths
• Component analysis results
• Session ID for correlation

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Agent 3: STAGING INSPECTOR (Staging Environment Audit)

Mode: REMOTE

Environment: staging.dss.overbits.luz.uy

Responsibilities:

1. Audit staging deployment
2. Collect browser logs from staging users
3. Capture runtime screenshots
4. Check for console errors
5. Analyze network performance
6. Compare staging vs local tokens

Tools Available:

• /dss-config set remote - Switch to REMOTE mode
• /dss-logs --session latest - Get browser logs
• /dss-screenshot .dashboard - Server-side screenshots
• /dss-errors --last 24h - Error analysis
• /dss-diagnostic --performance - Performance metrics
• Remote API strategy

Deliverables:

• Browser log analysis (errors, warnings)
• Staging screenshot collection
• Network performance report
• Error rate trends
• DOM snapshot analysis (Shadow State)

Session Data to Share:

• Session ID(s) from staging users
• Error logs categorized by severity
• Performance metrics
• Screenshot comparison baseline

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Agent 4: PRODUCTION MONITOR (Production Environment Audit)

Mode: REMOTE

Environment: dss.overbits.luz.uy (production)

Responsibilities:

1. Monitor production health
2. Analyze real user browser logs
3. Identify critical errors
4. Compare production vs staging
5. Visual regression detection
6. Performance benchmarking

Tools Available:

• /dss-config set remote - Switch to REMOTE mode
• /dss-logs --production --last 7d - Week of logs
• /dss-errors --severity critical - Critical errors only
• /dss-diagnostic --full - Complete system diagnostic
• /dss-screenshot --compare staging - Visual regression
• Remote monitoring tools

Deliverables:

• Production health dashboard
• Critical error report
• Visual regression findings
• Performance comparison (staging vs prod)
• User impact analysis

Session Data to Share:

• Production session IDs
• Critical error details
• Performance deltas
• Visual regression screenshots

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Agent 5: SYNTHESIZER (Cross-Environment Analysis)

Mode: Context-aware (analyzes data from all modes)

Responsibilities:

1. Aggregate findings from all agents
2. Identify cross-environment discrepancies
3. Correlate errors to root causes
4. Prioritize issues by impact
5. Generate comprehensive report
6. Create Q1 improvement roadmap

Tools Available:

• Task queue to fetch agent outputs
• Data correlation algorithms
• Report generation
• Prioritization framework

Deliverables:

• Executive Summary (1 page)
• Detailed Findings Report (by category)
• Cross-Environment Discrepancy Matrix
• Prioritized Issue Backlog
• Q1 Improvement Roadmap
• Visual Regression Gallery

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Challenge Phases

Phase 1: Setup & Planning (30 minutes)

Architect Agent Tasks:

1. Review challenge requirements
2. Create audit checklist
3. Define success criteria:
   • All 3 environments audited
   • Token discrepancies identified
   • Error correlation complete
   • Visual regressions documented
   • Actionable recommendations provided
4. Create task queue entries for each agent
5. Share coordination plan

All Agents:

• Verify DSS PowerTools plugin installed
• Check mode capabilities: /dss-status
• Confirm network access to remote environments
• Review session ID strategy

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Phase 2: Parallel Environment Audits (2-3 hours)

Local Scout (LOCAL mode):

# Switch to LOCAL mode
/dss-config set local

# Verify capabilities
/dss-status

# Audit components
/dss-audit components/ --deep

# Extract tokens
/dss-extract src/tokens/ --output local-tokens.json

# Capture Storybook screenshots
/dss-screenshot Button --story primary,secondary,disabled
/dss-screenshot Card --story default,elevated
/dss-screenshot Input --story default,error,disabled

# Analyze patterns
/dss-analyze components/ --patterns tokens,hardcoded,inconsistencies

# Check local console
/dss-logs --local --last 1h

# Export results
/dss-export-session local-audit-{timestamp}

Staging Inspector (REMOTE mode):

# Switch to REMOTE mode
/dss-config set remote

# Configure remote URL
export DSS_REMOTE_URL=https://staging.dss.overbits.luz.uy

# Verify connection
/dss-status

# Get browser logs from staging
/dss-logs --session latest --limit 500

# Find errors
/dss-errors --last 24h --severity high,critical

# Capture runtime screenshots
/dss-screenshot .dashboard --fullpage
/dss-screenshot .component-library

# Performance check
/dss-diagnostic --performance --compare local

# Get DOM snapshots (Shadow State)
/dss-snapshot --latest

# Export results
/dss-export-session staging-audit-{timestamp}

Production Monitor (REMOTE mode):

# Switch to REMOTE mode
/dss-config set remote

# Configure production URL
export DSS_REMOTE_URL=https://dss.overbits.luz.uy

# Health check
/dss-health --detailed

# Get production logs (7 days)
/dss-logs --last 7d --limit 1000

# Critical errors only
/dss-errors --severity critical --grouped

# Performance benchmarks
/dss-diagnostic --performance --baseline staging

# Visual regression vs staging
/dss-screenshot .header --compare staging
/dss-screenshot .footer --compare staging

# Monitor metrics
/dss-metrics --uptime --error-rate --performance

# Export results
/dss-export-session prod-audit-{timestamp}

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Phase 3: Data Correlation (1 hour)

Synthesizer Agent Tasks:

1. Fetch Agent Data:

# Via task queue
local_data = get_task_result("local-audit-{timestamp}")
staging_data = get_task_result("staging-audit-{timestamp}")
prod_data = get_task_result("prod-audit-{timestamp}")

2. Token Consistency Analysis:

# Compare token inventories
local_tokens = local_data['tokens']
staging_tokens = extract_tokens_from_logs(staging_data['logs'])
prod_tokens = extract_tokens_from_logs(prod_data['logs'])

discrepancies = find_discrepancies(local_tokens, staging_tokens, prod_tokens)

3. Error Correlation:

# Group errors by root cause
staging_errors = staging_data['errors']
prod_errors = prod_data['errors']

correlated = correlate_errors(staging_errors, prod_errors)
root_causes = identify_root_causes(correlated)

4. Visual Regression Analysis:

# Compare screenshots
local_screenshots = local_data['screenshots']
staging_screenshots = staging_data['screenshots']
prod_screenshots = prod_data['screenshots']

regressions = detect_visual_regressions(
    local_screenshots,
    staging_screenshots,
    prod_screenshots
)

5. Performance Comparison:

# Benchmark analysis
perf_matrix = {
    'local': local_data['performance'],
    'staging': staging_data['performance'],
    'production': prod_data['performance']
}

deltas = calculate_performance_deltas(perf_matrix)
bottlenecks = identify_bottlenecks(deltas)

---

Phase 4: Report Generation (1 hour)

Synthesizer Deliverables:

1. Executive Summary (1 page):

# Design System Audit: Cross-Environment Analysis

## Key Findings
- 12 token discrepancies between local and production
- 5 critical errors affecting 23% of production users
- 3 visual regressions in staging not present locally
- 18% performance degradation in production vs local

## Top 3 Priorities
1. Fix critical ButtonGroup error (23% user impact)
2. Align spacing tokens across environments (12 discrepancies)
3. Optimize Card component rendering (18% perf impact)

## Next Steps
- See detailed findings in full report
- Q1 roadmap attached

2. Detailed Findings Report:

• Token Discrepancies (by category: color, spacing, typography)
• Error Analysis (by severity, frequency, impact)
• Visual Regressions (with screenshot comparisons)
• Performance Benchmarks (by component, environment)
• Component Adoption Metrics

3. Cross-Environment Discrepancy Matrix:

   Component	Local	Staging	Production	Discrepancy
   Button	v2.1	v2.1	v2.0	Version mismatch
   Card	Tokens	Tokens	Hardcoded	Token usage
   Input	OK	OK	OK	Consistent

4. Prioritized Issue Backlog:

## P0 - Critical (Fix this sprint)
- [ ] ButtonGroup onClick error (23% users affected)
- [ ] Card spacing inconsistency (visual regression)

## P1 - High (Fix next sprint)
- [ ] Align spacing tokens (12 discrepancies)
- [ ] Optimize Card rendering (18% perf)
- [ ] Fix Input placeholder color mismatch

## P2 - Medium (Q1 roadmap)
- [ ] Standardize component props across environments
- [ ] Document token migration guide
- [ ] Add performance monitoring

5. Q1 Improvement Roadmap:

• Month 1: Fix critical errors and visual regressions
• Month 2: Token alignment and performance optimization
• Month 3: Documentation and monitoring improvements

---

Success Criteria

Technical Success

• All 3 environments successfully audited
• Mode switching worked seamlessly (LOCAL ↔ REMOTE)
• Session IDs enabled data correlation
• Browser logs captured from remote environments
• Screenshots compared across environments
• Performance metrics benchmarked

Collaboration Success

• 5 agents coordinated via task queue
• Data shared between agents successfully
• No duplicate work across agents
• Findings synthesized coherently

Business Success

• Actionable recommendations generated
• Issues prioritized by user impact
• Q1 roadmap created
• Executive summary delivered
• Visual evidence provided (screenshots)

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Bonus Challenges

1. Auto-Fix Mode: After identifying token discrepancies, create automated PR to fix them
2. Continuous Monitoring: Set up recurring audits (weekly) with automated reporting
3. Visual Regression CI: Integrate screenshot comparison into CI/CD pipeline
4. Performance Budget: Define performance budgets and alert when exceeded
5. Multi-Project Audit: Extend audit to multiple design system consumers

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Evaluation Rubric

Category	Points	Criteria
Environment Coverage	20	All 3 environments audited thoroughly
Mode Mastery	20	Correct LOCAL/REMOTE mode usage
Data Quality	15	Complete, accurate data collection
Correlation Accuracy	15	Correct cross-environment correlation
Agent Collaboration	10	Effective task queue coordination
Report Quality	10	Clear, actionable recommendations
Prioritization	5	Issues prioritized by impact
Visual Evidence	5	Screenshots and comparisons included

Total: 100 points

Passing Score: 70 points

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Example Agent Coordination (Task Queue)

# Architect creates coordination tasks
create_task({
    "title": "Local Environment Audit",
    "assigned_to": "local-scout",
    "description": "Audit local components and extract tokens",
    "priority": 1
})

create_task({
    "title": "Staging Environment Audit",
    "assigned_to": "staging-inspector",
    "description": "Audit staging deployment and browser logs",
    "priority": 1,
    "dependencies": []  # Can run in parallel
})

# Agents claim and complete tasks
claim_task("local-environment-audit")
start_task("local-environment-audit")

# ... perform audit ...

complete_task("local-environment-audit", result={
    "tokens": local_tokens,
    "screenshots": screenshot_paths,
    "session_id": "local-audit-xyz789"
})

# Synthesizer fetches results
local_results = get_task_result("local-environment-audit")

---

Tips for Success

1. Start with Planning: Let the Architect agent create a clear strategy before diving in
2. Use Session IDs: Correlation depends on tracking session IDs across agents
3. Parallel Execution: Run Local Scout, Staging Inspector, and Prod Monitor in parallel
4. Share Data Early: Don't wait until the end to share findings
5. Visual Evidence: Screenshots are crucial for demonstrating issues
6. Prioritize by Impact: Not all issues are equal - focus on user impact
7. Test Mode Switching: Verify LOCAL/REMOTE modes work before starting
8. Document Assumptions: Make assumptions explicit in reports

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Stretch Goals

1. Real-Time Dashboard: Create live dashboard showing audit progress
2. Automated Fixes: Generate PRs to fix identified issues
3. Slack Integration: Post findings to team Slack channel
4. Trend Analysis: Compare current audit to previous audits (3 months ago)
5. Cost Analysis: Estimate development cost to fix each issue

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Challenge Completion

When all agents have completed their work and the Synthesizer has generated the final report, submit the following:

1. Complete audit findings report
2. Cross-environment discrepancy matrix
3. Prioritized issue backlog
4. Q1 improvement roadmap
5. Screenshot gallery (regressions)
6. Agent coordination logs (task queue)

Good luck, agents! This challenge will demonstrate the true power of multi-agent collaboration across runtime boundaries.

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Challenge Created: 2025-12-06 Difficulty: EXPERT Estimated Duration: 4-6 hours Success Rate: TBD (first run)