validation-rules-builder

What This Skill Does

The validation-rules-builder is a powerful, extensible engine designed for construction professionals and data managers to ensure integrity across project datasets. Construction projects often ingest vast amounts of data from disparate systems, leading to errors in Work Breakdown Structures (WBS), cost codes, and Building Information Modeling (BIM) parameters. This skill allows you to define complex validation logic using predefined RegEx patterns or custom functions to enforce strict naming conventions and numerical thresholds. By validating input before it hits your primary database or ERP system, the builder significantly reduces the risk of project delays caused by mismatched data, invalid cost codes, or non-compliant schedule activities.

Installation

You can install the skill by executing the following command in your terminal:

clawhub install openclaw/skills/skills/datadrivenconstruction/validation-rules-builder

Ensure your environment has the necessary write permissions to the plugin directory to complete the installation successfully.

Use Cases

• Project Scheduling Integrity: Validate activity IDs against company-wide standards to prevent import failures in Oracle Primavera or Microsoft Project.
• Cost Control Automation: Verify cost codes against your chart of accounts to ensure that every invoice and expense report is correctly categorized before processing.
• BIM Data Governance: Check level names and grid line identifiers in BIM exports to ensure that spatial data matches the documentation standards required for structural analysis.
• Vendor Compliance: Ensure data provided by subcontractors adheres to internal file naming conventions for submittals and drawings.

Example Prompts

1. "Build a validation rule that ensures all 'cost_code' fields follow the format [Department Code]-[6 Digit Number] and flag any errors as 'WARNING'."
2. "Add a range validation rule to the 'budget_estimate' field to ensure that values are between 0 and 1,000,000, and return an error if the value exceeds this limit."
3. "Validate the 'drawing_number' column in my CSV upload using the standard drawing_number regex pattern and provide a summary report of all non-compliant rows."

Tips & Limitations

• Pre-defined Patterns: Always leverage the internal PATTERNS library first (e.g., date_iso, email, wbs_code) to ensure your validation aligns with industry best practices.
• Performance: For extremely large datasets (millions of rows), consider batching your validations to avoid memory overhead.
• Regex Complexity: If you are building highly complex custom patterns, test your RegEx strings in an external validator before implementing them to avoid false negatives.
• Severity Levels: Use 'WARNING' for non-critical formatting issues that need cleanup, but reserve 'ERROR' for critical identifiers like WBS codes that will cause downstream system failures.