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Cable Type Vision Identifier
x402
Cable Type Vision Identifier is a paid API for AI agents from material.halowerk.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-13).
Analyzes a cable photograph via OpenAI vision model to identify cable type candidates, conductor material, core count, and visible markings as structured JSON
Price / call$0.005
Success—
StatusUnknown
How this service works
Downloads one HTTPS image through the hub SSRF guard, then asks the configured OpenAI vision model for strict structured JSON. It reports observed features and readable markings, at most five ranked type candidates, and conductor material, core count or cross-section only where the image supports them; unknown values remain null or unknown. The result is identification assistance, not an electrical safety clearance, approval, voltage-state determination or substitute for inspection and testing.
Output
A structured JSON object containing: observed visual features of the cable, any readable text or markings on the cable jacket, up to five ranked cable type candidates with confidence ordering, conductor material (copper/aluminum/unknown), core count or cross-section where visually determinable, and null/unknown for any values the image does not support. The result is identification assistance only, not a safety clearance or electrical approval.
Example use cases
Field technician cable inventory audit
“I found an unmarked cable in the junction box and need to know what type it is before I proceed — can you analyze this photo and give me the top candidates for cable type and what the conductor material looks like? Image is at https://storage.example.com/site-photos/cable-jb-42.jpg”
Recycling facility scrap sorting
“We have a batch of cables coming in for recycling and I need to identify whether this one is copper or aluminum and estimate the core count from this photo: https://recycleyard.example.com/scrap/cable-item-221.png”
Electrical project material verification
“Before I order replacement cable, can you look at this image of the existing wiring and tell me the cable type, any readable markings, and the conductor cross-section if visible? Photo URL: https://myproject.example.com/photos/existing-wiring.jpg”
Technical details
Endpoint
POSThttps://material.halowerk.com/cable-type-visionWhen to prefer
Choose this endpoint when you have a publicly accessible HTTPS photo of a cable and need automated identification of its type, conductor material, or core count without manual lookup. It is purpose-built for cable-specific vision analysis with structured JSON output, unlike general-purpose vision APIs that require prompt engineering. It fits best in workflows involving field inspection, scrap sorting, material auditing, or procurement verification where a human photo is available but specification documentation is not.
Side effects
- Non-HTTPS image URL provided — rejected by SSRF guard
- Image URL is not publicly accessible or returns 4xx/5xx
- Image is not a cable photograph — vision model returns low-confidence or irrelevant results
- Image format is not JPEG, PNG, WebP, or non-animated GIF
- Image URL exceeds 2048 characters
- Cable markings are too obscured or image quality too low for readable extraction — values returned as null
- OpenAI vision model unavailable or rate-limited — upstream error propagated
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| image_url | string | Public HTTPS URL of one JPEG, PNG, WebP or non-animated GIF cable photograph. |
Tags
x402
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