Openclaw Usage Dashboard

---
name: openclaw-usage-dashboard
description: "Generate an interactive local HTML dashboard showing OpenClaw API usage, costs, and rate-limit quotas across multiple LLM providers (Anthropic, OpenAI, Google, Moonshot, Mistral, Cohere, Groq). Reads session transcripts directly — no external service needed. Use when a user asks about API costs, token usage, model spend, quota/rate limits, usage by model or time period, or wants a cost overview dashboard. Triggers on \"usage dashboard\", \"API kosten\", \"wie viel kostet\", \"kontingent\", \"rate limit\", \"token verbrauch\", \"cost dashboard\", \"openclaw costs\", \"spending overview\"."
---

# OpenClaw Usage Dashboard

Generate a self-contained HTML dashboard from OpenClaw session transcripts. Zero dependencies — Python 3.8+ stdlib only.

## Usage

```bash
# Real data (reads ~/.openclaw/agents/main/sessions/)
python3 scripts/usage-dashboard-generic.py [output.html]

# Demo mode (generates 30 days of realistic mock data)
python3 scripts/usage-dashboard-generic.py [output.html] --demo
```

Default output: `~/openclaw-usage-dashboard.html`

Override sessions path: set `OPENCLAW_ROOT` env var.

## What It Shows

- **Cost KPIs**: Total spend, today's cost, API calls, active model, cache hit rate, monthly projection
- **Model config**: Active / default / fallback models from `openclaw.json`
- **Anthropic quota gauges**: 5h and 7d rate limit utilization (requires `ANTHROPIC_API_KEY`)
- **Donut chart**: Cost distribution by model
- **Hourly sparkline**: Today's call volume by hour
- **Stacked bars**: Cost by period (daily / weekly / monthly / yearly)
- **Model table**: Per-model breakdown with token counts and cost
- **Detail table + chart**: Toggle between table and bar chart view per period
- **Budget tracker**: Set monthly limit, progress bar, localStorage persistence
- **CSV export**: Download any period view as CSV
- **Provider dropdown**: Filter by provider

## Supported Providers

Anthropic, OpenAI, Google, Moonshot/Kimi, Mistral, Cohere, Groq — 30+ models with built-in pricing.

## Customization

### Add models

Edit `PRICES` dict in the script (price per 1M tokens):

```python
"provider/model-name": {"input": 2.50, "output": 10.00, "cache_read": 1.25, "cache_write": 2.50}
```

Add to `MODEL_COLORS` and `ALIAS_MAP` as needed.

### Pricing reference

See `references/prices.md` for current prices across all providers.

## Requirements

- Python 3.8+ (stdlib only)
- `ANTHROPIC_API_KEY` in env (optional, for live quota gauges)