ClawHub

csv-cleanroom

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

Audits

Pending
ClawScanPass

Agentic behavior and permission review.

Static analysisPass

Pattern checks against bundled files.

VirusTotalPending

Multi-engine malware detections and file reputation.

Install

openclaw skills install csv-cleanroom

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.