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data-quality-checker

Name: data-quality-checker
Author: charlie-morrison

作者 charlie-morrison · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ✓ 安全检测通过

114

总下载

当前安装

版本数

在 OpenClaw 中安装

/install data-quality-checker

功能描述

Validate CSV, JSON, and JSONL data files for quality issues. Detects missing values, duplicates, type inconsistencies, statistical outliers, format violation...

使用说明 (SKILL.md)

Data Quality Checker

Validate CSV/JSON/JSONL data for quality issues. Pure Python, zero dependencies.

Quick Start

# Full quality check
python3 scripts/check_data_quality.py data.csv

# JSON/JSONL support
python3 scripts/check_data_quality.py data.json
python3 scripts/check_data_quality.py data.jsonl

# Markdown report
python3 scripts/check_data_quality.py data.csv --format markdown

# JSON report (for CI/CD)
python3 scripts/check_data_quality.py data.csv --format json

# Only specific checks
python3 scripts/check_data_quality.py data.csv --checks missing,duplicates,types

# Only warnings and critical
python3 scripts/check_data_quality.py data.csv --severity warning

# Save report
python3 scripts/check_data_quality.py data.csv --format markdown --output report.md

Schema Validation

# Generate schema from existing data
python3 scripts/check_data_quality.py data.csv --generate-schema schema.json

# Validate against schema
python3 scripts/check_data_quality.py data.csv --schema schema.json

Checks Performed

Check	Description	Severity
`missing`	Missing/null/empty values per column	info → critical
`duplicates`	Duplicate rows and potential ID conflicts	warning
`types`	Mixed data types within columns	info → warning
`outliers`	Statistical outliers via IQR method	info → warning
`formats`	Email/phone/URL/date format violations	warning
`whitespace`	Leading/trailing whitespace	info
`empty`	Entirely empty columns	warning
`drift`	Extra/missing keys across rows (schema drift)	warning

Quality Score

0-100 score based on weighted severity:

90-100: Clean data, minor issues
70-89: Usable but needs attention
50-69: Significant issues
0-49: Critical problems

Exit Codes

0 — No warnings or critical issues
1 — Warnings found
2 — Critical issues found

Use in CI: python3 scripts/check_data_quality.py data.csv || echo "Quality check failed"

Schema Format

JSON schema with validation rules:

{
  "required": ["id", "email", "name"],
  "properties": {
    "id": {"type": "integer", "minimum": 1},
    "email": {"type": "string", "pattern": "^[^@]+@[^@]+\\.[^@]+$"},
    "age": {"type": "number", "minimum": 0, "maximum": 150},
    "status": {"type": "string", "enum": ["active", "inactive", "pending"]}
  }
}

安全使用建议

This skill appears to do what it says: run the included Python script on local CSV/JSON files to produce a data‑quality report. Before installing or running on sensitive data: 1) review the entire scripts/check_data_quality.py file — the listing you provided is truncated, and I couldn't inspect the file tail where networking or other behavior could appear; 2) run it first on non-sensitive sample data in an isolated environment; 3) check memory/CPU behavior on large files (the tool appears in-memory and may not stream very large datasets); 4) prefer installing skills from a known/published source (owner and homepage are unknown and STATUS.md notes a price), and 5) if you need to use it in CI on sensitive datasets, consider adding monitoring or sandboxing and/or reimplementing core checks within your vetted tooling.

功能分析

Type: OpenClaw Skill Name: data-quality-checker Version: 1.0.0 The data-quality-checker skill is a legitimate utility for validating CSV and JSON data. The core logic in scripts/check_data_quality.py uses only Python standard libraries to perform statistical analysis, type inference, and schema validation. There are no signs of data exfiltration, network activity, command execution, or prompt injection attempts.

能力评估

✓ Purpose & Capability

Name/description match the included script: the code implements CSV/JSON/JSONL loading and the listed quality checks (missing, duplicates, types, outliers, formats, whitespace, empty, drift). No unrelated binaries, env vars, or services are requested.

✓ Instruction Scope

SKILL.md instructs running the included Python script against local data files and generating reports; the instructions do not ask the agent to read unrelated system files, credentials, or transmit data externally.

✓ Install Mechanism

No install spec (instruction-only + bundled script). This is low risk: nothing is downloaded or installed automatically by the skill.

✓ Credentials

The skill declares no required environment variables or credentials and the visible code does not access environment secrets or configuration. No excessive permissions are requested.

✓ Persistence & Privilege

The skill is not marked always:true and does not attempt to modify system or other skills' configurations in the visible code. Autonomous invocation is allowed (platform default) but not combined with other red flags.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install data-quality-checker
安装完成后，直接呼叫该 Skill 的名称或使用 /data-quality-checker 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Initial release

元数据

Slug data-quality-checker

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题