Analytics Page

Overview

Time window selector

• Last 24 hours
• Last 7 days
• Last 30 days
• All time

Cost dashboard

30-day consumption chart

• X-axis: Dates (last 30 days)
• Y-axis: Cost (USD)
• Bars: Daily spending
• Hover: See exact cost for each day

• Color coding:
  • 🟢 Green - Below average
  • 🟡 Yellow - Average
  • 🔴 Red - Above average
• Trend line: Overlaid to show direction
• Annotations: Mark significant events (deployments, incidents)

• Spot cost spikes
• Identify trends (increasing/decreasing)
• Correlate with deployments or changes
• Weekly patterns (weekdays vs weekends)

Total consumption

• Total Cost - Sum for selected time window
• Comparison - vs previous period
  • ⬆️ 15% increase
  • ⬇️ 10% decrease
  • ➡️ No change (< 2%)
• Projection - Estimated monthly cost (if trend continues)

Total Consumption (Last 30 days)
$567.89
⬆️ 15% vs previous 30 days
Projected monthly: ~$580

Daily breakdown table

• Date
• Runs - Count of runs
• Actions - Count of actions
• Cost - Total USD
• Avg Cost per Run - Mean cost
• Avg Cost per Action - Mean cost

• Click any column header to sort
• Default: Date (descending)

• Download as CSV for analysis in Excel/BI tools

Performance dashboard

Average metrics

$0.0123
⬇️ 5% vs previous period

523ms
➡️ No change vs previous period

37.2
⬆️ 8% vs previous period

Cost by action type

• Each slice = one action type
• Size = proportion of total cost
• Hover for exact amount
• Click to filter ledger by that action

• 🔵 call_llm: $234.56 (41%)
• 🟢 search_web: $123.45 (22%)
• 🟡 fetch_data: $89.12 (16%)
• 🟠 analyze_text: $67.89 (12%)
• Others: $52.87 (9%)

• Identify top cost drivers
• Focus optimization on largest slices
• Track changes over time

Cost by agent

• Agent names (Y-axis)
• Cost (X-axis)
• Sorted by cost (descending)
• Color-coded by relative cost

• Identify most expensive agents
• Compare agent efficiency
• Budget allocation by agent

Actions over time

• X-axis: Time (hours, days, or months based on window)
• Y-axis: Action count
• Multiple lines: Different action types

• Usage patterns (peak times)
• Growth trends
• Action mix changes

Cost optimization recommendations

High-cost actions

💡 Recommendation: Optimize LLM calls

Finding: "call_llm" accounts for 45% of costs ($234.56)

Suggestions:
• Reduce max_tokens from 1000 to 500 (potential savings: ~$100/month)
• Use gpt-4o-mini for simple queries (potential savings: ~$80/month)
• Implement response caching (potential savings: ~$50/month)

Total potential savings: $230/month (40%)

Inefficient patterns

⚠️ Warning: Redundant API calls detected

Finding: Agent "trading-bot" calls "fetch_price" avg 15 times per run

Suggestion: Cache price data for 5 minutes to reduce API calls

Potential savings: $45/month

Rate limiting opportunities

💡 Recommendation: Add rate limiting

Finding: "search_web" called 500+ times/day

Suggestion: Rate limit to 100 calls/hour to prevent runaway costs

Risk reduction: Prevents potential $1000+ cost incidents

Filters and segmentation

Filter by agent

• Compare costs across agents
• Focus on one agent’s performance
• Identify underutilized agents

Filter by action type

• Analyze LLM costs separately
• Track API call costs
• Compare tool usage

Group by

• By day - Daily breakdown
• By hour - Hourly breakdown (for 24h window)
• By week - Weekly breakdown (for 30d+ window)
• By month - Monthly breakdown (for all time)

Budget Forecasting & Alerts

Budget forecast widget

• Current Spend - What you’ve spent so far this period
• Burn Rate - Spending velocity relative to time elapsed
  • 1.0 = on track
  • > 1.0 = overspending
  • < 1.0 = underspending
• Projected Total - Estimated end-of-period spend
• Days Remaining - Time left in budget period

• 🟢 Info - On track (< 80% projected)
• 🟡 Warning - Approaching limit (80-100% projected)
• 🟠 Critical - Will exceed budget (100%+ projected)
• 🔴 Exceeded - Already over budget

Current Spend: $234.56 (46.9% of budget)
Burn Rate: 1.15x (overspending)
Projected Total: $575.23 of $500.00 budget
Days Remaining: 18 days

Smart recommendations

• “⚠️ Budget will be exceeded by $75.23 (15.0%)”
• ”🔥 High burn rate (1.15x) - reduce agent frequency or switch to cheaper models”
• ”💡 18 days remaining - time to optimize or increase budget”
• ”💰 Switch expensive actions to cheaper models (GPT-4 → GPT-3.5 saves 90%)”
• “⚙️ Implement rate limiting or approval gates for high-cost actions”

Budget exhaustion warning

• Projected date exceeded - When budget will run out
• Days until exceeded - Countdown to budget exhaustion
• Visual alert - Warning banner with urgency indicator

Spend trend chart

• Historical spend - Actual daily costs (solid line)
• Projected spend - Forecasted future costs (dashed line)
• Budget line - Budget limit reference (dotted line)

• Hover for exact daily amounts
• See cumulative spend over time
• Visual indication when projected to exceed budget
• Automatic period selection (defaults to current month)

Budget alerts

• Budget reaches 80% threshold
• Projected to exceed budget
• Budget already exceeded
• Burn rate exceeds 1.2x

• Severity level (warning/critical/exceeded)
• Current vs projected spend
• Days until exhaustion
• Quick recommendations

How forecasting works

daily_rate = current_spend / days_elapsed
projected_spend = daily_rate × total_days_in_period

• First few days: ~50% confidence
• Mid-period: ~70% confidence
• Late period: ~90% confidence

Setting budget periods

• Current month (default)
• Custom date range
• Rolling 30 days

GET /api/v1/budgets/forecast?budget=500.0&period_start=2025-01-01&period_end=2025-01-31

Budget alert emails

• Threshold alerts (at 80%, 90%, 100%)
• Daily budget summaries
• Weekly forecast updates
• Exceeded budget notifications

Common workflows

Monthly cost review

1. Select “Last 30 days” time window
2. Review total consumption
3. Check 30-day chart for spikes
4. Investigate anomalies:
   • Click spike day in chart
   • Filter Activity Ledger by that date
   • Review expensive actions
5. Check cost by action type pie chart
6. Read optimization recommendations
7. Implement suggested optimizations

Agent cost comparison

1. View “Cost by Agent” chart
2. Identify top 3 most expensive agents
3. For each agent:
   • Click bar to navigate to agent details
   • Review “Top Actions”
   • Check “Cost Breakdown”
   • Look for optimization opportunities
4. Compare with similar agents:
   • Why is Agent A 3x more expensive than Agent B?
   • Different usage patterns?
   • Different action mix?
   • Bugs or inefficiencies?

Track optimization impact

1. Note current “Avg Cost per Action” before optimization
2. Implement optimization (e.g., use cheaper model)
3. Wait 24 hours
4. Return to Analytics page
5. Compare “Avg Cost per Action”
6. Calculate savings:
   Daily savings = (Old avg - New avg) × Daily actions
   Monthly projection = Daily savings × 30
   
7. Document successful optimizations

Budget planning

1. Select “Last 30 days”
2. Note “Total Consumption”
3. Check “Projected monthly” estimate
4. Review “Cost by Agent” to allocate budgets
5. Set per-agent budgets in Settings → Policies
6. Monitor adherence in future periods

Identify usage patterns

1. View “Actions over time” chart
2. Look for patterns:
   • Peak usage times (optimize for these)
   • Weekend vs weekday differences
   • Growth trends (plan capacity)
   • Seasonal variations
3. Adjust:
   • Scale infrastructure for peaks
   • Budget for expected growth
   • Implement rate limiting during peaks

Export and reporting

Export charts

• PNG image - For presentations
• CSV data - For analysis
• PDF report - For stakeholders

Scheduled reports (future)

• Daily cost summary (email)
• Weekly trends analysis (email + Slack)
• Monthly executive summary (PDF)

Best practices

Keyboard shortcuts

• 1 - Switch to 24h view
• 7 - Switch to 7d view
• 3 - Switch to 30d view
• a - Switch to all time view
• e - Export current view

Troubleshooting

”Charts not loading”

• Check time window selector
• Verify you have runs in selected period
• Refresh page
• Try shorter time window

”No data for selected period”

• Extend time window (try “All time”)
• Check if any runs exist (Runs page)
• Verify agent is sending data

”Cost seems wrong”

• Check if multiple agents are included
• Verify time window is correct
• Review Activity Ledger for source data
• Check for currency/timezone mismatches

”Recommendations not showing”

• Recommendations appear after 7+ days of data
• Need minimum 100 actions for analysis
• Some patterns need 30 days to detect

See also

• Platform Stats API - API documentation
• Activity Ledger - Drill into specific actions
• Agents - Per-agent cost breakdown
• Settings - Configure budget policies