A Python-based rule engine designed to validate construction data, ranging from BIM metadata to cost codes and schedule IDs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install validation-rules-builder
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install validation-rules-builder using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Validation Rules Builder?
The Validation Rules Builder is a specialized toolset within the Openclaw Skills ecosystem designed to tackle the industry-wide problem of inconsistent construction data. It allows developers and data managers to define, manage, and execute complex validation logic using RegEx patterns, numeric ranges, and custom Python functions. By enforcing data standards at the point of entry or during transformation, it ensures that cost codes, WBS structures, and BIM element properties remain clean and actionable.
This skill is particularly valuable for teams managing large-scale project data where manual verification is impossible. Whether you are dealing with malformed drawing numbers or invalid schedule logic, this framework provides a structured approach to identifying and reporting data issues before they impact project outcomes.
Validation Rules Builder Use Cases
- Enforcing standardized WBS and cost code formatting across diverse project teams.
- Validating BIM element metadata (GUIDs, types, levels) for model coordination.
- Verifying schedule activity logic, such as ensuring start dates precede end dates.
- Cleaning document management data by checking drawing numbers and revision codes against project standards.
- Auditing financial records for quantity and unit cost range compliance.
How Validation Rules Builder Works
- Instantiate the ValidationRulesBuilder to begin defining your data quality requirements.
- Add specific validation rules (Regex, Range, Enum, or Custom) to target individual fields in your dataset.
- Utilize pre-defined industry patterns for common formats like cost codes and activity IDs provided by Openclaw Skills.
- Input your records as a list of dictionaries into the validation engine.
- Process the output results which categorize issues into errors, warnings, or info-level notifications for immediate remediation.
Validation Rules Builder Setup
To get started with this skill, ensure you have Python 3.x installed on your Darwin, Linux, or Win32 system.
# Verify python installation
python3 --version
# Integrate the builder into your local environment
# Copy the ValidationRulesBuilder class into your project directory
Then, import the builder in your script:
from validation_rules_builder import ValidationRulesBuilder, ConstructionValidators
Validation Rules Builder Data Schema & Taxonomy
The skill utilizes a structured metadata approach to classify validation issues and rule sets. The following table describes the primary data objects:
| Object | Key Fields | Purpose |
|---|---|---|
| ValidationRule | name, field, rule_type, pattern, severity | Defines the logic and threshold for a specific data check. |
| ValidationResult | field, is_valid, message, severity, value | Captures the outcome of a rule application on a specific record. |
| RuleType | REGEX, RANGE, ENUM, CUSTOM, REQUIRED | Categorizes the method of validation used. |
| Severity | ERROR, WARNING, INFO | Determines the critical nature of a validation failure. |
Validation Rules Builder Advanced Features
- Support for custom Python lambda functions to handle complex, multi-field business logic.
- Pre-built construction-specific validators for rapid deployment on BIM and schedule datasets.
- Batch validation mode providing detailed summaries including error counts and record indices.
- Reusable pattern library for common industry formats like ISO dates and email addresses.
- Flexible severity levels to allow for 'soft' warnings without blocking data processing pipelines.
SKILL.md
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