Individual skill
data-cleaning-pass
Clean a messy dataset methodically — the profiling pass that finds what's actually wrong (dupes, format drift, phantom spaces, mixed types), the fix order that doesn't corrupt while correcting, and the log that makes the cleaning defensible. Use when asked clean this export, why is my pivot double-counting, these names don't match between sheets, or prep this data for analysis. Produces the profile of what's wrong, the ordered cleaning plan, the join-key repairs, and the cleaning log.
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# Data Cleaning Pass Skill
Dirty data doesn't announce itself — it double-counts in the pivot, drops rows in the join, and averages text as zero. Cleaning done ad hoc corrupts as it corrects (the dedupe that removed real records, the find-replace that hit the wrong column). The pass is methodical: *profile first* (what's actually wrong, counted), fix in an order where each step doesn't mask the next, keep the original untouched, and log every transformation — because "how did you get these numbers" deserves an answer.
## What This Skill Produces
- **The profile** — per column: type consistency, blank/error counts, distinct-value sanity, the weirdest values surfaced
- **The cleaning plan** — ordered fixes with their methods, run on a copy
- **The join-key repair** — the match-rate before/after when sheets must link
- **The cleaning log** — what changed, how many rows/cells, by what rule — the defensibility artifact
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