Stop Burning Tokens — OpenClaw Cost Diagnostic Primerv1.0.0

A law firm processes 50+ client PDFs daily for contract review. Using raw PDFs instead of Markdown costs 20x more tokens. By converting to Markdown, capping conversations, and tiering models, they reduce token cost by ~8x while maintaining quality.

A SaaS company runs an OpenClaw chatbot handling 10,000 queries/day. Each query loads full conversation history and all plugins. By summarizing after 10 turns, caching system prompts, and disabling unused plugins, they cut costs from $8/session to $1/session.

A large enterprise uses agents to answer employee queries from a vast document repository. Without indexing, agents retrieve full documents wastefully. By indexing references and pre-processing context, they reduce input tokens by 8x and improve answer relevance.

A 10-person dev team uses agents for code review. Each agent call loads the entire codebase, ignoring model tiering. By scoping agents to minimal context and using cheaper models for simple checks, they save $1,750/month while keeping review accuracy.

Offer a monthly subscription where you audit a client's OpenClaw deployment, apply the diagnostic questions, and deliver a cost reduction report with actionable steps. Revenue comes from recurring monthly fees, typically $500-$2,000/month per client.

Provide one-time consulting engagements to restructure a client's agent pipelines, including caching setup, model tiering, and context scoping. Charge a project fee based on complexity, typically $5,000-$20,000 per engagement.

Develop and sell a diagnostic plugin or tool that automatically monitors token usage, flags inefficiencies, and suggests optimizations. Revenue via one-time purchase or subscription, priced at $50-$200/month per user.