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Linkfox Ruiguan Image Compliance

  • 166 installs
  • 64 repo stars
  • Updated August 3, 2026
  • linkfox-ai/linkfox-skills

Scan product images with Ruiguan for logo, trademark, and policy violations so galleries pass marketplace moderation before ads and organic traffic scale.

About

Uses Ruiguan to analyze product images for trademark, logo, and marketplace policy issues prior to listing activation. Helps agents batch-audit galleries, block non-compliant creatives, and prevent costly post-launch suppressions across ecommerce channels.

  • Ruiguan image trademark detection
  • Logo and brand mark violation flags
  • Gallery preflight before publish
  • Marketplace moderation risk reduction
  • Batch image compliance for catalogs

Linkfox Ruiguan Image Compliance by the numbers

  • 166 all-time installs (skills.sh)
  • Ranked #849 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-ruiguan-image-compliance

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Listed on Skillselion
Installs166
repo stars64
Last updatedAugust 3, 2026
Repositorylinkfox-ai/linkfox-skills

What it does

Scan product images with Ruiguan for logo, trademark, and policy violations so galleries pass marketplace moderation before ads and organic traffic scale.

Files

SKILL.mdMarkdownGitHub ↗

Ruiguan Policy Compliance Image Detection

This skill guides you on how to use the Ruiguan policy compliance detection tool to identify potential policy violations in product images. It performs image-based similarity search against a known database of prohibited products.

Core Concepts

Ruiguan Policy Compliance Image Detection is an image-based compliance screening service. Given a product image URL, it searches for visually similar products in a database of known policy-violating items. The tool returns matching violations ranked by visual similarity.

Similarity score (cosine): A value between 0 and 1. Higher values indicate stronger visual resemblance to known violating products. A score close to 1.0 means the product image is nearly identical to a flagged violation.

Parameter Guide

ParameterTypeRequiredDescriptionExample
Image URLimageUrlYesThe URL of the product image to check (max 1000 chars)https://example.com/product.jpg

Key notes:

  • The image URL must be publicly accessible
  • Supported formats include common image types (JPG, PNG, etc.)
  • The URL must not exceed 1000 characters

Response Fields

FieldAPI NameDescription
Total MatchestotalNumber of matching violation records found
Violation ListdataArray of matched violating products
Violation ImagepdImgOssUrlImage URL of the matched violating product
Similarity ScorecosineSimilarity between the input image and the violation (0~1)
Product Title (EN)pdTitleEnglish title of the matched violating product
Product Title (CN)pdTitleCHNCensoredChinese title of the matched violating product
Detection IDdetectIdUnique identifier for this detection session
Token CostcostTokenNumber of tokens consumed by this request

Local Image Upload

This tool requires a publicly accessible image URL. If the user provides a local image file path (e.g., C:\Users\...\photo.png, /home/.../image.jpg), you must upload it first to obtain a public URL.

Run the upload script:

python scripts/upload_image.py /path/to/local/image.png

The script will return a public URL (valid for 24 hours) that can be used as the image URL parameter.

Usage Examples

1. Basic compliance check for a single product image

Check this product image for policy compliance: https://example.com/images/product-123.jpg

2. Batch checking multiple product images

Please scan these product images for potential policy violations:
- https://example.com/images/item-a.jpg
- https://example.com/images/item-b.jpg

3. Pre-listing compliance screening

Before I list this product, can you check if the image triggers any policy flags?
Image: https://example.com/new-product.png

Display Rules

1. Show results in a clear table: Present each matched violation with its image, similarity score, and product titles 2. Highlight high-similarity matches: When the cosine score exceeds 0.8, clearly flag the result as a strong match that likely requires attention 3. Include violation images: When results contain pdImgOssUrl, display the matched violation image so the user can visually compare 4. Score interpretation: Always explain what the similarity score means -- higher values indicate closer resemblance to known violations 5. Error handling: When a query fails, explain the issue and suggest checking whether the image URL is valid and publicly accessible 6. No legal advice: Present detection results factually without providing legal conclusions; remind users to verify with platform policies

Important Limitations

  • Image-only detection: This tool works exclusively with image URLs; it does not analyze text descriptions or product metadata
  • URL accessibility: The image URL must be publicly reachable by the detection service
  • URL length cap: Image URLs must not exceed 1000 characters
  • Similarity-based: Results are based on visual similarity and do not constitute a definitive policy ruling

User Expression & Scenario Quick Reference

Applicable -- Image-based product policy compliance checks:

User SaysScenario
"Check if this product image has compliance risks"Single image compliance check
"Scan my product images for policy violations"Batch compliance screening
"Is this image flagged as a prohibited product"Specific violation inquiry
"Pre-screen my listing images for policy risks"Pre-listing compliance audit
"Find similar violations for this product image"Similarity-based violation search
"这个产品能安全上架吗"合规风险预检
"帮我检测一下这个图片是否违规"单图合规检测

Not applicable -- Needs beyond image-based policy compliance detection:

  • Text-based product compliance analysis
  • General product category classification
  • Intellectual property / trademark infringement
  • Patent or copyright detection (use other Ruiguan skills)

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply: 1. The functionality or purpose described in this skill does not match actual behavior 2. The skill's results do not match the user's intent 3. The user expresses dissatisfaction or praise about this skill 4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

<!-- LF_LARGE_RESPONSE_BLOCK -->

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/ruiguan_image_compliance_search.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"
Pick --out-dir outside any git working tree (e.g. /tmp/... on Unix, %TEMP%/... on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.
This skill exposes multiple entry scripts: ruiguan_image_compliance_search.py, upload_image.py. Pass --script scripts/<name>.py to choose the one you need.

run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

  • High field count per record, or fields you don't need
  • Batch/paginated results (multiple items per call)
  • Long-text fields (descriptions, reviews, HTML, time series)
  • Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read. <!-- /LF_LARGE_RESPONSE_BLOCK -->

--- For more high-quality, professional cross-border e-commerce skills, set [LinkFox Skills](https://skill.linkfox.com/).

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