Assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thres...
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install data-quality-checkOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install data-quality-checkβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/data-quality-check/π‘Extract and place the folder at the path above, then restart your agent.
Category
πData & AnalyticsPlatforms
What Data Quality Check can do for your AI workflow
Assess construction data directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 1,194+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Data Quality Check
Help me get started with Data Quality Check
Explains what Data Quality Check does, walks through the setup, and runs a quick demo based on your current project
Use Data Quality Check to assess construction data quality using completeness, accuracy, cons...
Invokes Data Quality Check with the right parameters and returns the result directly in the conversation
What can I do with Data Quality Check in my data & analytics workflow?
Lists the top use cases for Data Quality Check, with example commands for each scenario
Guides & tutorials for AI skills
Data Quality Check extends your AI assistant with the ability to assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thres... Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Data Quality Check as its underlying capability.
Data Quality Check works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Data Quality Check once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
To install Data Quality Check, copy the skill folder to `~/.claude/skills/data-quality-check/` for use across all your projects, or `.claude/skills/data-quality-check/` for a single project. Restart Claude and the skill is immediately active β invoke it with `/data-quality-check` or just describe your goal and the AI will pick it up automatically.
Data Quality Check has been installed 1,194 times, making it one of the more actively used skills in the Data & Analytics category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/data-quality-check/ for personal use (all projects), or .claude/skills/data-quality-check/ for project-specific use. Restart your AI client, then invoke with /data-quality-check or let the AI discover it automatically.
Data Quality Check supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Data Quality Check is free to install. Check the repository for licensing information.
Assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thres...
Automate my data & analytics tasks using Data Quality Check
Identifies repetitive steps in your workflow and sets up Data Quality Check to handle them automatically
MCP vs traditional plugins: what's the difference?
Data Quality Check is categorized under Data & Analytics. These skills help AI agents perform specialized tasks in this domain.