token-estimator

What This Skill Does

The token-estimator is an essential utility for OpenClaw users who prioritize cost-efficiency and performance monitoring. This skill calculates the precise Token footprint for any given input before it is sent to an LLM. By leveraging specialized tokenizers—such as tiktoken for OpenAI models and AutoTokenizer for Qwen and HuggingFace models—it provides granular, real-time consumption metrics. The skill doesn't just calculate; it acts as a proactive advisor, offering actionable insights like '4D Compression' suggestions to significantly slash token usage by up to 70% for long-form inputs, ensuring you stay within your budget while maintaining high-quality outputs.

Installation

To integrate this utility, ensure you have the OpenClaw environment initialized. Run the following command in your terminal:

clawhub install openclaw/skills/skills/largetool/token-estimator

Ensure your system meets the dependency requirements by verifying the installation of tiktoken, transformers, and dashscope packages via pip3.

Use Cases

1. Budget Optimization: Developers and power users can use this to gauge the cost of complex API requests before executing them, preventing surprise billing.
2. Long-Context Management: When processing large documents or logs, the tool flags excessive token density and suggests compression to keep prompts within model context windows.
3. Analytics & Monitoring: Keep track of your usage patterns via the 'Token Water Meter', which visualizes historical consumption over hourly, daily, and monthly periods, helping you optimize your workflow frequency.

Example Prompts

1. "/token How much will it cost to process this 5000-word research paper using qwen3.5-plus?"
2. "/token-estimate Analyze the potential savings for this code block if I enable 4D compression."
3. "/count What is the remaining token balance for my current subscription cycle?"

Tips & Limitations

For models that are not natively supported by the internal mapping, the tool falls back to a 4-character-per-token heuristic. While this is accurate to within ±10%, it is always safer to use explicitly defined model aliases (like gpt-4 or dashscope/qwen3.5-plus) for mission-critical budget calculations. Always monitor the 'Water Meter' to ensure your usage remains within your platform's specific quotas.