ClawHub

csv-cleanroom

v1.0.0

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

⭐ 0· 266·0 current·0 all-time
byvx：17605205782@52yuanchangxing

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for 52yuanchangxing/csv-cleanroom.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "csv-cleanroom" (52yuanchangxing/csv-cleanroom) from ClawHub.
Skill page: https://clawhub.ai/52yuanchangxing/csv-cleanroom
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required binaries: python3
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Canonical install target

openclaw skills install 52yuanchangxing/csv-cleanroom

ClawHub CLI

Package manager switcher

npx clawhub@latest install csv-cleanroom
Security Scan
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Benign
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OpenClawOpenClaw
Benign
high confidence
✓
Purpose & Capability
Name/description (CSV profiling and cleanup planning) align with the included artefacts: a small Python helper script and a checklist resource. Declared runtime requirement is only python3, which is proportionate to the stated purpose.
✓
Instruction Scope
SKILL.md restricts behavior to profiling, schema-normalization guidance, and producing plans/preview artifacts. It references only the local script and resource file. The bundled script only reads the explicitly provided CSV path and writes a JSON profile output; SKILL.md emphasizes preview-first and avoiding destructive actions unless the user asks.
✓
Install Mechanism
No install spec is present (instruction-only skill with a local script). This is low-risk: nothing is downloaded or executed from remote hosts and the helper script is local and auditable.
✓
Credentials
The skill declares no environment variables, credentials, or config paths. The Python script does not access environment secrets or external services. Requested inputs (CSV path, target schema, etc.) match the functionality.
✓
Persistence & Privilege
always is false and the skill does not request persistent/privileged agent presence or modify other skills. Autonomous invocation remains platform-default and is not a specific red flag here.
Assessment
This skill appears to be a local, auditable CSV profiling and planning tool. Before installing/using it: (1) review scripts/csv_cleanroom.py yourself — it writes a profile JSON (default csv_profile.json) to the working directory and could overwrite that file if present; (2) run the helper in a safe/isolated folder if your CSVs contain sensitive data; (3) remember the skill will not perform destructive edits by default — require explicit confirmation before applying changes; (4) ensure python3 is on PATH. If you need stronger guarantees, run the script manually on a copy of your data first.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🧰 Clawdis
Binspython3
latestvk97dghdwrx75b6ews08b4y8prx82sz57skillvk97dghdwrx75b6ews08b4y8prx82sz57
266downloads
0stars
1versions
Updated 1mo ago
v1.0.0
MIT-0
vx：17605205782@52yuanchangxing
latestskill
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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.

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