AI prompt mining here means organizing and evaluating prompt candidates for a defined application task. It is not cryptocurrency proof of work. These guides focus on the parts that make a prompt useful to another developer: representative inputs, explicit criteria, reproducible comparisons, versioned records, and clear failure handling.
Start with evaluation before building automation. Once a candidate meets your own criteria, follow the workflow guide to define its input contract and release history. The public JSON examples illustrate record shapes and fictional test metadata; they do not call a model provider. Use them to build and test a consumer before connecting an authorized execution environment.
Prompt API Workflows: Version, Test, and Release
Give prompt records stable identities, explicit input contracts, controlled execution, and evaluation evidence that another developer can inspect.
Read the field guide 7 min ↗
AI Prompt Mining: Evaluate Before You Automate
Move from interesting prompt candidates to reproducible decisions with representative test cases, versioned rubrics, and failure analysis.
Read the field guide 7 min ↗