An intelligent AI agent skill designed to audit food packaging labels for regulatory compliance using computer vision and industry standards.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install label-compliance-audit
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 label-compliance-audit 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 Label Compliance Audit?
The Label Compliance Audit is a specialized tool within the ecosystem of Openclaw Skills that automates the rigorous process of reviewing food packaging labels. By leveraging advanced image recognition and PDF analysis, the skill ensures that design drafts adhere to critical mandatory standards such as GB7718 and GB28050. It acts as a digital compliance officer, identifying missing mandatory information, validating nutritional claims, and checking formatting requirements to mitigate legal and regulatory risks.
This skill is particularly valuable for quality assurance teams and designers who need to verify complex data like allergen labeling, font size constraints, and background contrast. By integrating these capabilities into your workflow, Openclaw Skills allow for a faster, more accurate transition from design to production while maintaining strict adherence to food safety and labeling laws.
Label Compliance Audit Use Cases
- Automated auditing of food packaging design drafts for regulatory compliance.
- Validation of nutritional information and NRV (Nutrient Reference Value) calculations.
- Verification of mandatory allergen labeling and specific font size requirements.
- Cross-referencing marketing claims like sugar-free or low-fat against actual ingredient data.
How Label Compliance Audit Works
- The agent ingests a design draft in image or PDF format and extracts all text and visual elements using OCR and vision capabilities.
- It identifies key metadata including product name, ingredient lists, net weight, and manufacturer details.
- The skill performs a multi-layered audit using either autonomous reasoning or a predefined checklist stored in the assets folder.
- It references specific regulatory documents to verify mandatory labels, formatting, and nutritional accuracy.
- A structured audit report is generated, highlighting non-compliance items, risk levels (Serious, General, Slight), and suggested corrections.
Label Compliance Audit Setup
To deploy this within your environment using Openclaw Skills, ensure the following directory structure and reference files are available to the agent:
# Ensure reference documents are in the /references folder
# gb7718-standard.md
# gb28050-standard.md
# claims-guideline.md
# Ensure the audit checklist is in the /assets folder
# audit-checklist.md
No external API dependencies are required as the skill utilizes native AI vision and reasoning capabilities.
Label Compliance Audit Data Schema & Taxonomy
| Component | Description | Format |
|---|---|---|
| OCR Extraction | Raw text and visual data captured from design files | JSON/String |
| Reference Standards | Regulatory rules for GB7718 and GB28050 | Markdown |
| Audit Checklist | Itemized list for step-by-step verification | Markdown |
| Audit Report | Final output including risk assessment and fix suggestions | Structured Markdown |
Label Compliance Audit Advanced Features
- Multi-modal support for both high-resolution images and multi-page PDF design drafts.
- Specialized NRV calculation engine to mathematically verify energy, protein, and fat percentages according to GB28050.
- Risk-level categorization (Serious/General/Slight) for prioritized remediation.
- Context-aware claim verification to ensure descriptive terms meet specific threshold conditions.
SKILL.md
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