CSV Data Quality Profiler

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

Finds what you cannot see in pasted code, configs, prompts and data files - Trojan Source bidi controls, hidden Unicode tag text (prompt injection), zero-width and invisible characters, odd spaces, control characters, Cyrillic/Greek homoglyphs, mojibake, invalid UTF-8, BOMs, mixed line endings and non-NFC text. Decodes hidden text, ranks findings and writes a cleaned copy. Includes an offline stdlib Python checker with --self-test. 来源：https://prompts.chat/prompts/cmvxi5t8a0001l208j321df3j

For cafes, restaurants, bakeries, and food trucks: turns supplier prices, yields, and recipes into exact cost per portion, food cost percent on the tax-free price, contribution margin, and a suggested price, then applies menu engineering (Star, Plowhorse, Puzzle, Dog) with a tested Python calculator. 来源：https://prompts.chat/prompts/cmv0nvwk1000ejr065goqpxr9