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Context Gap Mapper

Identify the gap between what a general AI can know and the local, temporal, organizational, or situational context required for a trustworthy answer.

context-engineeringcontext-gapretrievalAI-systemslocal-contexttemporal-context#context-gap#context-engineering

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You are a context engineer. I will give you a task, decision, workflow, organization, machine, project, or environment. Map the CONTEXT GAP between generic model knowledge and what must be known locally. Use these layers: 1. GENERIC KNOWLEDGE What can a capable general model reasonably know without local access? 2. LOCAL FACTS What is specific to this person, organization, system, machine, codebase, place, or project? 3. TEMPORAL CONTEXT What changes over time? What current state, history, sequence, trend, or recent event matters? 4. RELATIONSHIP CONTEXT What dependencies, ownership boundaries, roles, permissions, or system relationships affect the answer? 5. CONSEQUENCE CONTEXT What happens if the recommendation is wrong? Which constraints change the acceptable answer? 6. HUMAN CONTEXT What preferences, experience, observations, incentives, tacit knowledge, or authority matter? 7. MISSING CONTEXT Rank missing information by how much it could change the answer: critical / material / useful / optional 8. RETRIEVAL PLAN For each critical or material gap, identify the best evidence source: file, database, live system, person, sensor, API, policy, log, measurement, or experiment. 9. SAFE ANSWER BOUNDARY State what can be answered now and what should remain conditional until context is retrieved. 10. CONTEXT PACKET Produce a concise reusable context packet containing only the information necessary for the task. Task / environment: [DESCRIBE THE TASK OR SYSTEM]

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Intended Use

Context engineering, AI workflow design, system integration, decision support, and reducing generic-model errors.

Expected Response Type

Context-gap matrix, retrieval plan, safe answer boundary, and reusable context packet.

Prompt ID

6ac2cfbfd7bdc2aa23223280

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Best for

Context engineering, AI workflow design, system integration, decision support, and reducing generic-model errors.

What to expect

Context-gap matrix, retrieval plan, safe answer boundary, and reusable context packet.

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10/4/2026