A specialized data governance tool designed to unify disparate classification systems while preserving alias mappings and deprecated terms.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install taxonomy-normalizer
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 taxonomy-normalizer 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 Taxonomy Normalizer?
Taxonomy Normalizer is a dedicated tool within the Openclaw Skills ecosystem built to solve the complexity of fragmented data structures. It serves as a bridge between different team vocabularies and database schemas, ensuring that conflicting classification systems are harmonized into a single, cohesive source of truth without losing historical context.
The skill focuses on identifying overlaps, managing deprecated terms, and providing safe migration paths. By prioritizing auditability and human-in-the-loop verification, it ensures that data normalization remains a controlled process rather than an automated risk to production environments.
Taxonomy Normalizer Use Cases
- Unifying classification systems from multiple teams or different database tables.
- Maintaining complex alias mappings and tracking deprecated terminology.
- Resolving category conflicts and overlaps during data integration projects.
- Generating structured migration suggestions for data governance workflows.
How Taxonomy Normalizer Works
- The skill reorganizes user-provided raw information into a formal task specification.
- It identifies and explicitly lists any missing information or items requiring human confirmation.
- A reviewable draft is generated to visualize proposed mappings and changes.
- Upon approval, it produces an executable checklist or runs a normalization script.
- The final output is structured into existing categories, conflicts, primary suggestions, and alias mappings.
Taxonomy Normalizer Setup
To use this skill, ensure you have python3 installed. You can run the normalization script via the CLI:
# Run the taxonomy normalization script
python3 "{baseDir}/scripts/run.py" --input <input_file> --output <output_file>
If the environment restricts script execution, the skill will generate the structured text directly based on the provided resources/spec.json.
Taxonomy Normalizer Data Schema & Taxonomy
The skill utilizes a standardized directory structure and specific file schemas for processing:
| File Path | Description |
|---|---|
{baseDir}/resources/spec.json |
The core specification and rule definitions. |
{baseDir}/resources/template.md |
The standardized output format for reports. |
{baseDir}/examples/ |
Sample input and output files for reference. |
{baseDir}/tests/smoke-test.md |
Validation test cases for the skill. |
All mappings include fields for Existing Categories, Conflict Analysis, Recommended Primary Category, Alias Mappings, and Deprecated Terms.
Taxonomy Normalizer Advanced Features
- Multi-OS compatibility supporting Darwin, Linux, and Win32 environments.
- Safe-mode execution that provides dry-run scenarios to prevent accidental production changes.
- Integration with Openclaw Skills protocols for structured task reorganization.
- Support for custom migration logic and compliance boundary descriptions for high-risk data environments.
SKILL.md
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