Show HN: PromptQL – Solving Context Size and Accuracy Issues in LLM Tool Calling

PromptQL is a programmatic approach to LLM tool composition which has shown remarkable improvement in accuracy (~2x) and repeatability (~4x) when compared to traditional tool calling and chaining approaches.

Fundamentally, PromptQL separates the creation of a query plan from the execution of the query plan. PromptQL uses the LLM to first create a program to compose the different tool calls hence avoiding the challenges with in-context tool chaining like accuracy, repeatability and context limits.