API Cost Tracker

Monitor and optimize your LLM API spending directly from your agent.

Quick Start

Run cost analysis:

python3 scripts/cost_tracker.py --summary

Commands

Check Current Spend

python3 scripts/cost_tracker.py --provider openai --period today
python3 scripts/cost_tracker.py --provider anthropic --period week
python3 scripts/cost_tracker.py --all --period month

Set Budget Alert

python3 scripts/cost_tracker.py --set-budget 100 --period month --alert telegram

Cost Breakdown by Model

python3 scripts/cost_tracker.py --breakdown model --period week

Optimization Recommendations

python3 scripts/cost_tracker.py --optimize

This analyzes usage patterns and recommends:

• Model downgrades for simple tasks (e.g., use Haiku instead of Opus for classification)
• Caching opportunities (repeated similar prompts)
• Batch processing windows (off-peak pricing where available)
• Context window optimization (trim unnecessary context)

Supported Providers

| Provider | Method | Setup | |----------|--------|-------| | OpenAI | Usage API | OPENAI_API_KEY env var | | Anthropic | Usage API | ANTHROPIC_API_KEY env var | | Google AI | Billing API | GOOGLE_API_KEY env var | | DeepSeek | Usage API | DEEPSEEK_API_KEY env var |

Budget Alerts

Configure in ~/.openclaw/cost-tracker.json:

{
  "budgets": {
    "daily": 10,
    "weekly": 50,
    "monthly": 200
  },
  "alertChannels": ["telegram", "discord"],
  "alertThresholds": [50, 75, 90, 100]
}

Alerts fire at each threshold percentage. At 100%, optionally pause non-critical agent tasks.

Output Format

Reports generate as markdown tables suitable for any messaging surface:

Provider    | Model              | Tokens    | Cost
------------|--------------------|-----------|---------
Anthropic   | claude-opus-4-6   | 2.1M      | $63.00
Anthropic   | claude-sonnet-4-6 | 5.4M      | $16.20
OpenAI      | gpt-4o            | 1.8M      | $9.00
            | TOTAL              |           | $88.20

Advanced: Cost Optimization Patterns

See references/optimization-guide.md for detailed strategies on reducing API spend by 30-60% without sacrificing quality.