# myAibd — AI Learning and Discovery Demo

> Synthetic AI learning and tool-discovery catalogue with local drafts. No live model calls, AI assistant or continuously verified tools catalogue.

- Canonical URL: https://khanai.co.technology/
- Methodology & Equations: https://khanai.co.technology/methodology/
- Interactive Browser Runtime: https://khanai.co.technology/run/
- Author & Root Entity: Mohammad Rezwan Khan, PhD (https://mrkhan.co.technology/#person)
- Ecosystem Directory: https://mklab.co.technology/
- Knowledge Graph JSON-LD: https://khanai.co.technology/knowledge-graph.jsonld

## Governing Mathematical Formulation & Units
- Formula: `Capability Readiness Rubric R = (Task_Fit + Verification_Ease + Privacy_Safety + Cost_Predictability) / 4`
- Units: Rubric dimensions scored on 1–5 integer scale; prompt/workflow drafts stored locally in browser JSON.

## Reproducible Worked Example
AI Workflow Evaluation Example: Evaluating a bilingual research-summarization workflow against the 4-factor verification rubric checks whether claims require primary-source citation, whether sensitive data is excluded, and how hallucination risk is mitigated—all executed locally without calling any live LLM API.