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csv-cleanroom
作者
vx：17605205782
· GitHub ↗
· v1.0.0
· MIT-0
287
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install csv-cleanroom
功能描述
Profile messy CSV files, standardize columns, detect data quality issues, and produce a reproducible cleanup plan.
使用说明 (SKILL.md)
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
- Profile the CSV: row count, nulls, duplicates, type mismatches, and outliers.
- Normalize headers and map to the target schema.
- Generate a step-by-step cleanup plan and optional transformed output.
- Document irreversible operations before applying them.
- 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.
安全使用建议
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.
功能分析
Type: OpenClaw Skill
Name: csv-cleanroom
Version: 1.0.0
The csv-cleanroom skill is a legitimate utility for profiling and cleaning CSV files. The Python script (scripts/csv_cleanroom.py) performs basic data analysis using standard libraries without any network access, obfuscation, or dangerous execution patterns. The instructions in SKILL.md are well-defined, focus strictly on the stated data processing task, and include safety-oriented operating rules such as preferring simulation modes and avoiding destructive actions without user consent.
能力评估
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.
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 csv-cleanroom - 安装完成后，直接呼叫该 Skill 的名称或使用
/csv-cleanroom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
csv-cleanroom 1.1.0
- Adds skill metadata, including required binary (python3) and emoji identifier.
- Expands on supported workflow: CSV profiling, schema normalization, cleanup planning, and quality scoring.
- Documents expected inputs (e.g., known bad values, dedupe rules, locale).
- Clarifies output contract: profile report, normalized schema, cleanup plan, quality scorecard.
- Provides guidance for safe use, including preview mode and boundaries on operations.
- Introduces default scripts and resources for local, auditable processing.
元数据
常见问题
csv-cleanroom 是什么？
Profile messy CSV files, standardize columns, detect data quality issues, and produce a reproducible cleanup plan. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 287 次。
如何安装 csv-cleanroom？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install csv-cleanroom」即可一键安装，无需额外配置。
csv-cleanroom 是免费的吗？
是的，csv-cleanroom 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
csv-cleanroom 支持哪些平台？
csv-cleanroom 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 csv-cleanroom？
由 vx：17605205782（@52yuanchangxing）开发并维护，当前版本 v1.0.0。
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