csv-cleanroom

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name: csv-cleanroom description: Profile messy CSV files, standardize columns, detect data quality issues, and produce a reproducible cleanup plan. version: 1.1.0 metadata: openclaw: requires: bins: - python3 emoji: 🧰

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CSV Cleanroom

Purpose

Profile messy CSV files, standardize columns, detect data quality issues, and produce a reproducible cleanup plan.

Trigger phrases

清洗 CSV

profile this dataset

数据质量检查

列名规范化

build a cleanup plan

Ask for these inputs

CSV file or schema

target schema if available

known bad values

dedupe rules

date/currency locale

Workflow

1. Profile the CSV: row count, nulls, duplicates, type mismatches, and outliers. 2. Normalize headers and map to the target schema. 3. Generate a step-by-step cleanup plan and optional transformed output. 4. Document irreversible operations before applying them. 5. Return a quality score and remediation checklist.

Output contract

profile report

normalized schema

cleanup plan

quality scorecard

Files in this skill

Script: {baseDir}/scripts/csv_cleanroom.py

Resource: {baseDir}/resources/data_quality_checklist.md

Operating rules

Be concrete and action-oriented.

Prefer preview / draft / simulation mode before destructive changes.

If information is missing, ask only for the minimum needed to proceed.

Never fabricate metrics, legal certainty, receipts, credentials, or evidence.

Keep assumptions explicit.

Suggested prompts

清洗 CSV

profile this dataset

数据质量检查

Use of script and resources

Use the bundled script when it helps the user produce a structured file, manifest, CSV, or first-pass draft. Use the resource file as the default schema, checklist, or preset when the user does not provide one.

Boundaries

This skill supports planning, structuring, and first-pass artifacts.

It should not claim that files were modified, messages were sent, or legal/financial decisions were finalized unless the user actually performed those actions.

Compatibility notes

Directory-based AgentSkills/OpenClaw skill.

Runtime dependency declared through metadata.openclaw.requires.

Helper script is local and auditable: scripts/csv_cleanroom.py.

Bundled resource is local and referenced by the instructions: resources/data_quality_checklist.md.