ClawCache Free
Smart LLM cost tracking and caching for Python
Why use this skill?
Slash your LLM API expenses with ClawCache Free. Monitor usage, track tokens, and implement smart SQLite caching to save money and improve response performance.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/abyousef739/clawcache-freeWhat This Skill Does
ClawCache Free is a specialized Python library designed to optimize LLM operations by providing granular cost monitoring and intelligent response caching. In a production environment where API costs can quickly scale, this skill acts as a financial middleware. It automatically logs every API request, calculates token usage with precision (incorporating 2026 pricing models), and stores responses in a local SQLite database to prevent redundant API calls. By checking the cache for exact-match requests based on parameters like model, temperature, and prompt content, it significantly reduces expenditures—demonstrating a proven 58.3% cache hit rate in simulated environments. It provides both an intuitive Python API for developers and a robust CLI for generating daily cost reports.
Installation
To integrate ClawCache into your OpenClaw environment, use the OpenClaw skill manager. Run the following command in your terminal:
clawhub install openclaw/skills/skills/abyousef739/clawcache-free
Once installed, ensure you have your respective LLM provider API keys configured in your environment variables, as the library will leverage these to perform its tracking functionality.
Use Cases
ClawCache is ideal for high-frequency LLM applications. Developers building chatbot interfaces, automated code review tools, or data analysis pipelines benefit most. It is particularly effective for scenarios where prompts are repeated or where the same system prompts are sent to different users. By implementing the provided decorators, you can achieve "free" responses for repeated queries, effectively optimizing your cloud infrastructure spend while maintaining sub-millisecond response times for cached data.
Example Prompts
- "Analyze my current daily LLM spend and show me the total amount saved using ClawCache over the last 48 hours."
- "Configure the ClawCache monitor to track my OpenAI and Anthropic usage separately and generate a CSV report for my monthly budget review."
- "Identify which of my recent prompts had the lowest cache hit rate and suggest ways to normalize those requests for better efficiency."
Tips & Limitations
To maximize efficiency, ensure you are using consistent parameter settings (temperature, top_p) for similar tasks, as the cache key depends on these values. While the SQLite storage is highly reliable for local or containerized applications, note that this is a local cache. If you are deploying across a distributed microservices architecture, you may need to map the database volume to a shared persistent storage solution. Always ensure your environment variable TIKTOKEN_ENCODING is set correctly for your specific models to ensure the token counting remains accurate as new models are released.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-abyousef739-clawcache-free": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-read, file-write, external-api