data-cleaning

95 / 100 · Low risk

Fine to try.

By magnus919/agent-skills (GitHub) · data · 172 stars · scanned at commit da4ce5c

Clean, profile, validate, reshape, and document messy tabular, text, JSON, and relational data through an evidence-first, reproducible workflow. Use when preparing data for analysis, reporting, modeling, ingestion, migration, or matching, including AI-suggested repair, entity-match review, score calibration limits, and reversible repair ledgers. Do not use for statistical modeling, dashboard design, or operating a named data platform; route those tasks to data-scientist, data-engineering, or th…

Works with any agent that supports SKILL.md skills.

What this skill can do

Runs commands on your computer

The author does not mention this.

Found in 6 places.

data-cleaning/scripts/test_profile_dataset.py, line 16output = json.loads(subprocess.check_output([sys.executable, str(SCRIPT), str(source)], text=True))
data-cleaning/scripts/test_profile_dataset.py, line 28overwrite = subprocess.run([sys.executable, str(SCRIPT), str(source), "--output", str(source)], capture_output=True, text=True)
data-cleaning/scripts/test_profile_dataset.py, line 29invalid = subprocess.run([sys.executable, str(SCRIPT), str(source), "--max-rows", "0"], capture_output=True, text=True)

Show 3 more

data-cleaning/scripts/test_reconcile_dataset.py, line 18result = json.loads(subprocess.check_output([sys.executable, str(SCRIPT), str(before), str(after), "--key", "id", "--sum", "amount"], text=True))
data-cleaning/scripts/test_reconcile_dataset.py, line 33overwrite = subprocess.run([sys.executable, str(SCRIPT), str(before), str(after), "--key", "id", "--output", str(output_alias)], capture_output=True, text=True)
data-cleaning/scripts/test_reconcile_dataset.py, line 38result = subprocess.check_output([sys.executable, str(SCRIPT), str(empty), str(empty), "--key", "id"], text=True)

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'data-cleaning' ] || [ -L ~/.agents/skills/'data-cleaning' ]; then echo 'A skill folder named data-cleaning already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/magnus919/agent-skills' "$d" && git -C "$d" checkout --quiet 'da4ce5c6823cce6da80f4e09c84998a4928402c1' -- 'data-cleaning' && mkdir -p ~/.agents/skills && cp -R "$d"/'data-cleaning' ~/.agents/skills/'data-cleaning' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'data-cleaning' ~/.claude/skills/'data-cleaning' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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Score history

Date	Version	Score
2026-11-09	`da4ce5c`	95
2026-11-07	`34a4d62`	100