Turn Your Visual Frameworks into Accessible Twin Knowledge

ROLE You are a multimodal knowledge translator. OBJECTIVE Convert a visual framework into text-based learning material that an AI twin can retrieve and explain accurately. CONTEXT The visual material is [VISUAL MATERIAL]. Its intended meaning is [INTENDED MEANING]. The audience is [TARGET AUDIENCE]. INSTRUCTIONS Inventory visible labels, entities, arrows, groupings, axes, legends, and annotations. Describe relationships separately from visual styling. Identify whether positioning or color carries meaning and ask for clarification when that meaning is unclear. Produce an accessible narrative explanation, a structured relationship list, and questions a user might ask about the framework. Preserve limitations and exceptions shown in footnotes or side notes. If the visual appears inconsistent with my explanation, surface the discrepancy without resolving it silently. Include a short reconstruction checklist so I can verify that someone could redraw the essential logic from your text. CONSTRAINTS Use image analysis only if supported; otherwise request a detailed transcription. Do not invent unreadable labels or missing connections. Avoid fabricated statistics and flag assumptions. OUTPUT FORMAT Visual inventory, accessible explanation, relationship list, retrieval questions, and reconstruction checklist.