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在 OpenClaw 中安装
/install data-quality-operations
功能描述
Data quality validation patterns for daily checks and anomaly follow-up.
使用说明 (SKILL.md)
Data Quality Operations
Use when dataset freshness/completeness checks must be run consistently.
Inputs to Gather
- Primary target (service, team, or dataset)
- Current impact and urgency
- Assigned owner and deadline
Core Commands
dq profile --dataset \x3Cname>dq validate --rule-set \x3Cid>dq anomaly --open --metric \x3Cname>workflow checklist --from templates/checklist.mdworkflow report --from templates/report.md
Operating Notes
- Prefer explicit owner assignment before action.
- Keep timeline notes concise and timestamped.
- Save output artifacts for audit and handoff.
- This version adds a structured report template for post-task summaries.
Version marker: data-quality-operations 1.2.0
安全使用建议
This skill appears to be a set of runbooks/templates for data-quality checks and is internally consistent. Before installing, verify what the 'dq' and 'workflow' commands are on your system (which binaries or services they map to), and confirm you trust those tools — they will perform the actual work and might require credentials or network access. Also note the small naming inconsistencies (package name/version/healthcheck text) which look like copy-paste errors; they are not dangerous but you may want to ask the publisher to correct them for clarity.
功能分析
Type: OpenClaw Skill
Name: data-quality-operations
Version: 1.2.0
The skill bundle provides standard templates and command definitions for data quality monitoring and reporting. The scripts (echo-version.sh, healthcheck.sh) are trivial and harmless, and the instructions in SKILL.md are strictly aligned with the stated purpose of dataset validation and reporting without any signs of malicious intent, data exfiltration, or prompt injection.
能力评估
Purpose & Capability
The SKILL.md, templates, and tiny helper scripts are coherent with a data-quality operations checklist/reporting skill. However, the top-level name shown as "1.2.0" and the healthcheck script echoing a different skill name ("pipiwu-benchmark-delta-skill") look like copy-paste or packaging lapses—these are sloppy but not inherently dangerous.
Instruction Scope
Runtime instructions are limited to running external commands (dq profile/validate/anomaly and workflow checklist/report) and using included templates; the SKILL.md does not instruct reading unrelated system files or exporting data to unknown endpoints. Note: the actual behavior depends on what the external 'dq' and 'workflow' binaries/tools do—those tools could contact services or require credentials, but that is outside this skill's files.
Install Mechanism
There is no install spec and only two tiny shell scripts plus templates are included. No downloads or archive extraction are present.
Credentials
The skill declares no required environment variables, no credentials, and the SKILL.md does not reference any secrets or unexpected env vars. This is proportionate for a checklist/reporting template skill.
Persistence & Privilege
The skill is not always-enabled and does not request elevated persistence. Model invocation is allowed (default), which is normal for user-invocable skills and not a 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 data-quality-operations - 安装完成后，直接呼叫该 Skill 的名称或使用
/data-quality-operations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
v1.2.0
- Added a structured report template for post-task summaries.
- Introduced the command: workflow report --from templates/report.md.
- Updated documentation to reflect new reporting workflow.
- Minor updates to asset and script files for version 1.2.0.
v1.1.0
- Added an operations checklist template for handoffs.
- Introduced `workflow checklist --from templates/checklist.md` to core commands.
- Updated operating notes to reflect new checklist template.
- Minor updates to scripts and documentation for version 1.1.0.
v1.0.0
Initial release providing core data quality validation operations:
- Introduces daily dataset freshness and completeness check patterns.
- Supports commands for profiling, rule-based validation, and anomaly monitoring.
- Guides on owner assignment, urgency tracking, and auditing outputs.
- Targeted for consistent quality monitoring and anomaly follow-up.
元数据
常见问题
1.2.0 是什么？
Data quality validation patterns for daily checks and anomaly follow-up. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 399 次。
如何安装 1.2.0？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install data-quality-operations」即可一键安装，无需额外配置。
1.2.0 是免费的吗？
是的，1.2.0 完全免费（开源免费），可自由下载、安装和使用。
1.2.0 支持哪些平台？
1.2.0 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 1.2.0？
由 Yikun Fu（@jiarani）开发并维护，当前版本 v1.2.0。
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