Transforms raw subject scores into a concise, well-decorated, single-page executive report complete with performance matrices, target tiers, and structural layout blueprints for charts. 来源：https://prompts.chat/prompts/cmr4nd4pv0001jl04slyzaozb
Checks CSV time series (metrics, sensor readings, sales by hour) for data problems before you chart or alert on them: missing intervals, duplicate or out-of-order timestamps, empty values, flatlines from stuck exporters, robust median/MAD spikes, and counter resets. Use when a dashboard looks wrong, before training a forecast, or when asking "is this data complete?". Includes a stdlib Python checker with --self-test. 来源：https://prompts.chat/prompts/cmvexglly000rjr088nxj0x8r
Compares two CSV exports of the same records (old vs new, billing vs ledger, source vs warehouse) by key after normalizing headers, delimiters, currency formats, accounting negatives, dates and case. Reports added, removed and duplicate keys, key format drift, changed values per column with tolerances, possible re-keys and a control-total bridge, then writes a reconciliation report. Includes a stdlib Python checker with --self-test. 来源：https://prompts.chat/prompts/cmvrsgiov0017jt07ksqlpubk
