prediction-trackinglisted

# Prediction Tracking Skill Track predictions made by AI researchers and critics, evaluate their accuracy over time. ## Prediction Recording When recording a new prediction, capture: ### Required Fields - **text**: The prediction as stated - **author**: Who made it - **madeAt**: When it was made - **timeframe**: When they expect it to happen - **topic**: What area of AI - **confidence**: How confident they seemed ### Optional Fields - **sourceUrl**: Where the prediction was made - **targetDate**: Specific date if mentioned - **conditions**: Any caveats or conditions - **metrics**: How to measure success ## Evaluation Status When evaluating predictions, assign one of: ### `verified` Clearly came true as stated. - The predicted capability/event occurred - Within the stated timeframe - Substantially as described ### `falsified` Clearly did not come true. - Timeframe passed without occurrence - Contradictory evidence emerged - Author retracted or modified claim ### `partially-verified` Partially accurate. - Some aspects came true, others didn't - Capability exists but weaker than claimed - Timeframe was off but direction correct ### `too-early` Not enough time has passed. - Still within stated timeframe - No definitive evidence either way ### `unfalsifiable` Cannot be objectively assessed. - Too vague to measure - No clear success criteria - Moved goalposts ### `ambiguous` Prediction was too vague to evaluate. - Multiple interpretations possible - Success criteria un