prompt-token-analyzerA Node.js CLI tool that analyzes prompt token usage using a GPT-compatible tokenizer. Helps agents estimate prompt size, debug context overflow, and optimize...
Install via ClawdBot CLI:
clawdbot install putixiaosheng/prompt-token-analyzerGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses system directories or attempts privilege escalation
sudo mvAudited Apr 18, 2026 · audit v1.0
Generated Mar 21, 2026
A customer service platform uses the analyzer to monitor prompt sizes in automated response systems, ensuring they stay within model limits and reducing token costs by trimming unnecessary context. This helps maintain efficient operations while handling high volumes of inquiries without exceeding budget constraints.
An e-learning company integrates the tool to analyze prompts for generating personalized study materials, optimizing token usage to keep costs low while providing tailored educational content. This enables scalable production of learning resources without compromising quality or exceeding financial limits.
Law firms employ the analyzer to pre-process legal documents before feeding them into LLMs for summarization or research, ensuring context windows are not exceeded and token costs are minimized. This streamlines legal workflows by preventing overflow errors and managing expenses effectively.
Marketing agencies use the tool to evaluate prompt sizes for generating ad copy or social media content, optimizing tokens to reduce costs while maintaining creative output. This allows for iterative testing of different prompts without incurring high API expenses.
Healthcare researchers utilize the analyzer to check token counts in prompts for analyzing medical records or research papers, ensuring efficient use of LLMs within budget and context limits. This supports data-driven insights while controlling operational costs in sensitive environments.
Offer a basic free version of the analyzer for individual developers, with premium features like batch processing and advanced analytics available through subscription plans. This model attracts users with no upfront cost and generates recurring revenue from enterprises needing higher capabilities.
Sell customized licenses to large organizations for integrating the analyzer into their internal AI pipelines, providing dedicated support and compliance features. This model targets businesses with high-volume token usage, ensuring steady income through annual contracts.
Provide consulting services to help companies implement and optimize the analyzer within their existing systems, offering training and custom development. This model leverages expertise to generate project-based revenue while building long-term client relationships.
💬 Integration Tip
Integrate the analyzer early in development pipelines to catch token overflow issues before deployment, using it as a pre-processing step in CI/CD workflows for cost-effective AI operations.
Scored Jun 19, 2026
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