I shipped a prompt that silently exploded our API bill — so I built a linter for prompts

A few weeks ago one of my prompts failed in production. Nothing crashed. No errors were thrown. But overnight, our API bill spiked because the prompt started generating extremely long responses. At first I assumed it was a model change or config issue. But after digging in, the real problem was simpler: We had no way to validate prompts before they ran. We lint code. We test code. But most teams don’t analyze prompts. So I built a small CLI tool called CostGuardAI . It analyzes prompts before they run and flags structural risks like: prompt injection / jailbreak surface instruction ambiguity conflicting directives unconstrained outputs (hallucination risk) token explosion / context misuse The idea is simple: treat prompts like code and run static analysis on them. Example npm install -g @camj78/costguardai costguardai analyze my-prompt.txt It outputs a CostGuardAI Safety Score (0–100, higher = safer) and highlights what’s driving the risk. The goal isn’t to predict exact model behavior