Documentation Index
Fetch the complete documentation index at: https://docs.appliedaifoundation.org/llms.txt
Use this file to discover all available pages before exploring further.
What it does
The Image Analysis skill runs AI vision over any image — a single photo, a folder, or a vessel inspection set — and produces a structured assessment. It auto-detects whether the image is maritime (equipment, machinery, vessel surfaces) and switches between two modes:- General mode — describes subject, objects, context, and any visible text
- Vessel mode — assesses equipment condition, detects defects, classifies severity, renames photos to descriptive filenames, and writes a searchable index
When to use it
- “Analyze this image”
- “What is this?”
- “Describe photo”
- “Process vessel photos”
- “Analyze the inspection batch”
- “What equipment is in this photo?”
Modes
General mode
For ad-hoc images. Returns a plain-language description: subject, key objects, environment, any readable text, useful context. Good for screenshots, document captures, quick “what am I looking at?” checks.Vessel mode
For inspection photo sets. The skill:- Classifies the equipment shown (engine room, deck, accommodation, cargo system, etc.)
- Rates equipment condition on a 5-point scale: good / fair / poor / damaged / critical
- Identifies visible defects with location and likely cause
- Suggests a descriptive filename so photos become self-explanatory in the file system
- Writes a structured index entry covering equipment, condition, defects, and metadata
How it works
The skill calls a unified vision engine (Gemini or OpenRouter, depending on configuration) with mode-specific prompts and configuration. Maritime detection runs first; if maritime content is present, vessel mode kicks in automatically. For large batches, the user is asked first which file action to take — rename in place, create renamed copies, or analyze without changing files.What it produces
| Mode | Output |
|---|---|
| General | Plain-language description per image |
| Vessel | Per-image equipment classification, condition rating, defect list, suggested filename, JSONL index of the whole batch |
Why it’s split into two modes
Generic image-description prompts produce vague results on engineering photos; condition-rating prompts produce nonsense on screenshots. Detecting the domain first, then routing to the right prompt, gets useful output for both cases without forcing the user to specify mode.Related skills
- pdf-vision-extractor — paired skill for diagrams and tables inside PDFs
- image-generator — counterpart for generating images instead of analysing them