Agents / Skills
Dual-Model Verification Workflow
A self-correcting multi-model agent loop that verifies AI claims against source material.
Description
This workflow uses two models in a feedback loop to eliminate hallucinations. A primary model performs research or data tasks, while a secondary checker model validates every claim by citing exact lines from the source; if a claim fails, the task is sent back to the primary model for revision until it passes.
Descriptions, tags, and model credits may be AI-generated or inferred from public sources and can be incomplete or wrong. Learn more.