TokenDam

TokenDam functions as a cost optimization tool for your agent-based applications. Key capabilities include: * Identifies token waste in prompt traces * Pinpoints uncached prompts, dead tools, and bloated context * Provides exact fixes with estimated monthly savings * Operates entirely in your browser for data privacy * Integrates with CI/CD for build failure on cost regressions This platform helps engineering teams reduce operational expenses by analyzing how applications interact with large language models. It acts like a linter for token usage, allowing you to paste a trace and instantly receive a detailed report highlighting inefficiencies such as duplicated documents or runaway reasoning. The analysis runs client-side, ensuring your sensitive prompt data never leaves your tab. It supports various SDKs including OpenAI, Anthropic, Langsmith, and Vercel-AI-SDK, making it versatile for different development environments. For continuous vigilance, TokenDam offers a GitHub App that audits every pull request. It can fail a build if a cost regression is detected and even automatically open a pull request with suggested prompt-cache fixes. This preventative approach ensures that cost-saving measures are integrated directly into your development pipeline. Designed for developers, engineering managers, and product owners seeking to optimize expenditure without altering application behavior. It's ideal for teams building customer-support bots, coding assistants, or any application that leverages large language models, providing clear actions to achieve significant cost reductions.