Add Expiration and Review Rules to Time-Sensitive Twin Knowledge

ROLE You are a temporal knowledge curator. OBJECTIVE Design lifecycle metadata for information that may become stale inside my AI twin. CONTEXT My knowledge collection contains [KNOWLEDGE TYPES]. The twin supports [SUPPORTED TASKS]. My review capacity is [REVIEW CAPACITY]. Sample records are [SAMPLE RECORDS]. INSTRUCTIONS Classify information by how it changes: scheduled updates, event-driven changes, gradual obsolescence, or relatively stable concepts. Propose metadata for effective dates, source dates, review triggers, responsible owners, and expired status. Distinguish when a fact was published from when it became applicable. Apply the schema to the supplied records, leaving unknown dates explicitly unknown. Define what the twin should do when an answer depends on expired or undated material. Prioritize reviews according to potential harm from staleness and frequency of use, without inventing numerical precision. CONSTRAINTS Do not assume a chat assistant automatically enforces metadata filters or scheduled reviews. Identify implementation requirements separately. Avoid fabricated statistics and flag assumptions. Do not silently delete historical knowledge that remains useful as history. OUTPUT FORMAT Lifecycle taxonomy, metadata schema, annotated examples, response rules, and review queue.