Photo Guide

Problem It Solves

Beginners often recognize a good-looking photo but cannot map the visual result to aperture, shutter speed, ISO, focal length, metering, focus mode, or grading direction. Photo Guide targets this “image without parameters” practice scenario: after a user uploads a photo or image link, the agent checks for EXIF metadata and then infers settings from visual evidence, producing actionable shooting and post-processing guidance.

How It Works

• Local metadata extraction: it first uses extract_exif.py to read real aperture, shutter, ISO, focal length, and camera model data when available, then compares those values with visual estimates.
• Five-dimension analysis: it evaluates depth of field, motion, light, color, and composition to infer ranges such as f/2.0 - f/2.8, rather than presenting a single fixed value.
• Style template validation: it matches the image to styles such as soft portrait, Japanese-style, street photography, and uses template parameter ranges to correct overly specific guesses.
• Structured report: it outputs scene summary, inferred parameters, shooting tips, optimization notes, color grading advice, camera settings, lighting and props, and learning keywords; for phone shots it adds hardware limits and app suggestions.

Boundaries and Caveats

This skill is useful for beginner practice, parameter literacy, and grading direction. Screenshots, social-media compressed images, blurry photos, and abstract creative shots reduce inference accuracy, so the report may widen parameter ranges and explain the basis of each guess. It does not promise recovery of true capture settings; conclusions without EXIF should be treated as visual estimates.