food-analyzer

Food Analyzer

Intent

Analyze food photos, labels, meals, and ingredient lists with nutrition, fitness, glycemic, processing, and interaction context.

Do Not Use When

• Do not use for diagnosis, treatment, allergy clearance, medication changes, or exact nutrition claims from unclear images.
• Required context is missing and cannot be reasonably inferred.
• A more specific skill in this repo is a better match.

Workflow

1. Identify the exact task and available source material.
2. Apply the domain rules and output format in this skill.
3. State assumptions, uncertainty, and missing inputs clearly.
4. Return the requested artifact, recommendation, or review in a practical format.
5. Check the result against the validation checklist before finishing.

Constraints

• Do not fabricate missing facts, measurements, dates, sources, or user context.
• Keep output aligned with Mick's direct, practical communication style unless the skill says otherwise.
• Preserve safety, legal, medical, financial, and operational boundaries stated in this file.
• Prefer concise, usable output over broad explanation.

Analyze images of food, plated meals, nutrition labels, or ingredient lists and return a structured nutritional breakdown with fitness, glycemic, processing, and interaction context.

Trigger When

• The user starts with fa or food
• The user uploads an image of food, a meal, a label, or an ingredient list
• The user asks to analyze food, scan a label, estimate calories or macros, check blood sugar impact, or check medication compatibility
• The user wants two foods or meals compared
• The user wants repeated meal patterns reviewed across multiple analyses

Input Modes

Detect which mode applies from the visible input:

Mode	What Claude Sees	Behavior
Meal or Plate	Actual food, plated dish, restaurant item	Estimate calories and macros from visual portion heuristics
Nutrition Label	FDA-style Nutrition Facts panel	Extract exact values from the label
Ingredient List	Text ingredients	Flag allergens, additives, and processing red flags
Mixed	Label and product both visible	Prefer label data over visual estimates
Comparison	Two foods, two labels, or two meals visible or described	Compare tradeoffs side by side before giving a recommendation
History Review	Multiple prior meals or repeated food summaries provided	Find patterns across repeated analyses rather than analyzing one item only