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Get Started Free →datadrivenconstruction/n8n-photo-report
Automate construction photo report generation using n8n with AI-powered image analysis.
Passed 17 of 22 test cases with the skill, and 7 of 22 without it.
and 9 more in the full report
11 fixed6 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
In the n8n JS parsing code for AI responses, if a photo's work activity doesn't match concrete, steel, or mep, what fallback category keyword should be assigned?
| Checked | Without skill | With skill |
|---|---|---|
| Assigns category GENERAL when work activity does not match concrete, steel, or mep | Missed | Passed |
The instructions your model reads when the skill loads.
Site photos require organization, analysis, and reporting. This workflow automates photo collection, AI analysis, and report generation.
[Photo Upload] → [AI Analysis] → [Categorization] → [Report Generation] → [Distribution]
{
"nodes": [
{
"name": "Photo Webhook",
"type": "n8n-nodes-base.webhook",
"parameters": {
"httpMethod": "POST",
"path": "photo-upload",
"options": {
"binaryData": true
}
}
},
{
"name": "Watch Dropbox Folder",
"type": "n8n-nodes-base.dropbox",
"parameters": {
"operation": "listFolder",
"path": "/SitePhotos/{{$today}}"
}
}
]
}
test cases passed, vs 7 / 22 without
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