API Cost Tracker

Analyze and optimize AI API costs across multiple providers with detailed breakdowns, trend detection, and actionable savings recommendations.

Quick Start

# Analyze OpenRouter usage (from activity page export)
python3 scripts/api_cost_tracker.py openrouter --file activity.json

# Analyze OpenAI usage (from billing export)
python3 scripts/api_cost_tracker.py openai --file usage.json

# Analyze from environment (auto-detect provider from API keys)
python3 scripts/api_cost_tracker.py auto --days 30

# Cost breakdown by model
python3 scripts/api_cost_tracker.py openrouter --file activity.json --by model

# Cost breakdown by day with trend analysis
python3 scripts/api_cost_tracker.py openrouter --file activity.json --by day --trends

# Find most expensive requests
python3 scripts/api_cost_tracker.py openrouter --file activity.json --top 20

# Compare current vs optimized (model substitution analysis)
python3 scripts/api_cost_tracker.py openrouter --file activity.json --optimize

# Set budget alert threshold
python3 scripts/api_cost_tracker.py openrouter --file activity.json --budget 50.00

# Output as markdown report
python3 scripts/api_cost_tracker.py openrouter --file activity.json --output markdown

# Output as JSON
python3 scripts/api_cost_tracker.py openrouter --file activity.json --output json

Supported Providers

| Provider | Input Format | Auto-detect | |----------|-------------|-------------| | OpenAI | Billing CSV/JSON export, API responses | OPENAI_API_KEY | | Anthropic | Usage API, console export | ANTHROPIC_API_KEY | | OpenRouter | Activity JSON, API responses | OPENROUTER_API_KEY | | Google AI | Billing export | GOOGLE_AI_API_KEY | | Generic | CSV with columns: timestamp, model, tokens_in, tokens_out, cost | N/A |

Analysis Features

1. Cost Breakdown — by model, day, week, feature/tag, request type
2. Trend Detection — spending velocity, anomaly detection, projected monthly cost
3. Optimization Report — model substitution suggestions, caching opportunities, prompt compression candidates
4. Budget Alerts — daily/weekly/monthly thresholds with projected overrun warnings
5. Top Spenders — most expensive individual requests or sessions
6. Model Comparison — cost-per-quality analysis using common benchmarks

Output Formats

• Terminal (default) — colored tables and charts
• Markdown — report suitable for documentation
• JSON — structured data for programmatic use
• CSV — spreadsheet-compatible export

How It Works

The script:

1. Reads usage data from the specified source (file, API, or environment)
2. Normalizes all entries to a common format (timestamp, model, input_tokens, output_tokens, cost)
3. Applies current provider pricing to calculate/verify costs
4. Groups and aggregates by the requested dimension
5. Runs optimization analysis comparing current models to cheaper alternatives
6. Generates the report in the requested format

Pricing Database

Built-in pricing for 50+ models (updated March 2026). Override with --pricing custom_prices.json.

Requirements

• Python 3.8+
• No external dependencies (stdlib only)