food-nutrition-facts-search

Searches nutrition facts, food scores, and packaged product data via public AI-friendly endpoints. Invoke when users ask to find, compare, or inspect foods, nutrition facts, brands, or barcodes.

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Install skill "food-nutrition-facts-search" with this command: npx skills add charliex2/food-nutrition-facts-search

Nutrition Facts Search

Use this skill when the user wants nutrition facts, food scores, product details, or barcode lookup data from a public food data website rather than codebase analysis.

When To Invoke

Invoke this skill when the user:

  • asks to find a food or packaged product
  • provides a brand name, barcode, or partial product name and wants the matching item
  • wants to compare two or more foods or products using nutrition facts or food scores
  • wants a structured summary of a food or product detail page

Do not invoke this skill for repository code search, implementation questions, or unrelated websites.

Public Endpoints

  • Search: https://foodbenchmark.com/api/ai/search?q=<query>&type=<all|foods|products>&limit=<1-20>&offset=<0-based>
  • Food detail: https://foodbenchmark.com/api/ai/foods/<slug>
  • Product detail: https://foodbenchmark.com/api/ai/products/<code>

Food vs Product

  • food means a generic food concept or food entry such as banana, olive oil, or broccoli
  • product means a product record that can expose label-style fields such as nutrition facts, ingredients, additives, brand, barcode, and packaging data
  • These are different datasets and should not be treated as interchangeable records
  • foods are best for generic food entities, category-level food scores, and food-oriented summaries
  • products are best for packaged items and for any request that needs nutrition-facts-style label data
  • Important rule: if the user asks for nutrition facts, nutrition label, calories, protein, fat, carbs, serving-based nutrients, or similar nutrient fields for a specific item, use products
  • Even when the user names a broad food such as whole milk or banana, if the intent is to inspect nutrition facts, use products because only product records expose nutrition facts in this workflow
  • If the user wants an ingredients list, ingredient analysis, additive details, or barcode lookup, use products only
  • If the user wants a generic food entry or food score summary without asking for nutrition facts, prefer foods
  • If the user names a brand, barcode, or a specific packaged item, prefer products
  • If the user says only something ambiguous like Coca-Cola, oat milk, or cookies, search all first and then disambiguate

Type Selection Rules

Choose type based on user intent, not only the wording of the item name.

  • Use type=products when the user asks for nutrition facts, nutrition labels, calories, macros, serving-based nutrients, ingredients, additives, barcode results, or a packaged/branded item
  • Use type=products when the user wants nutrition facts for a specific food name, because only product records provide nutrition facts in this workflow
  • Use type=foods when the user wants a generic food entry, food category context, or summary food scoring data and is not asking for nutrition facts
  • Use type=all when the query is ambiguous and intent is unclear, then choose the most relevant result set after search

Quick intent mapping:

  • Find banana nutrition facts -> type=products
  • Show whole milk calories -> type=products
  • Compare oat milk nutrition labels -> type=products
  • Find banana food score -> type=foods
  • What category is olive oil in? -> type=foods
  • Coca-Cola -> type=all

Workflow

1. Search First

Always call the search endpoint before requesting details.

  • Use type=products when the user asks for nutrition facts or any label-style nutrient data
  • Use type=products when the user clearly wants a packaged product, brand, ingredient list, additive data, or barcode result
  • Use type=foods when the user clearly wants a generic food entity or food score summary and is not asking for nutrition facts
  • Use type=all when the query is ambiguous

Search returns compact result groups:

  • foods: matched food records
  • products: matched product records
  • meta: totals, pagination, and truncation information

2. Fetch Details Only When Needed

After search:

  • If a single obvious result exists, fetch its detail endpoint
  • If several close matches exist, show the best matches first and ask the user to choose
  • If the user wants comparison, fetch detail for each selected item

3. Keep Responses Compact

  • Prefer structured summaries over raw JSON dumps
  • Include the canonical website URL for each selected entity
  • When product detail includes identity.siteUrl, recommend that the user open it to view the full page details
  • Mention when results are truncated or ambiguous
  • If nothing matches, say so clearly and suggest a narrower query

Output Shape

For foods, prioritize:

  • title
  • category
  • Food Compass 2
  • Health Star Rating
  • Nutri-Score
  • NOVA group
  • canonical URL

For products, prioritize:

  • title
  • brand
  • Nutri-Score
  • NOVA group
  • environmental score summary
  • ingredient/additive highlights when relevant
  • canonical URL

Query Strategy

  • Barcode-only input: use type=products
  • Nutrition-facts requests for any named item, including a food name: use type=products
  • Clearly food-like input without nutrition-facts intent: use type=foods
  • Ingredients, additives, or packaged-label questions: use type=products
  • Ambiguous names such as brands or broad product names: use type=all
  • If results are truncated, summarize the best matches and mention that more results exist
  • When you need additional pages, keep the same q and type, then advance with offset (or page)

Platform Rules

  • Use only public URLs from foodbenchmark.com
  • Do not depend on local files, local scripts, or IDE-only context
  • Do not dump raw Open Food Facts JSON unless the user explicitly asks for raw data
  • Prefer a short structured answer over long prose
  • When nothing matches, say that clearly and suggest a narrower query or a barcode

Recommended Response Format

For a single match:

  • entity name
  • entity type: food or product
  • key scores
  • 1 short interpretation sentence if useful
  • canonical URL
  • For product details, mention that the user can open identity.siteUrl to view the full detail page

For multiple matches:

  • show the top matches first
  • include enough fields for disambiguation
  • ask the user which one to inspect if there is no clear winner

Examples

Find nutrition facts for a food name

User: Find whole milk nutrition facts

  1. Request https://foodbenchmark.com/api/ai/search?q=whole%20milk&type=products
  2. If a clear product match exists, request https://foodbenchmark.com/api/ai/products/<code>
  3. Return a short summary with the canonical URL

Find a product by barcode

User: Check barcode 3017620422003

  1. Request https://foodbenchmark.com/api/ai/search?q=3017620422003&type=products
  2. If found, request https://foodbenchmark.com/api/ai/products/3017620422003
  3. Return the matched product with key scores and link

Compare products

User: Compare Coca-Cola and Pepsi nutrition facts

  1. Search both names
  2. If multiple matches exist, identify the best candidates
  3. Fetch details for the chosen products
  4. Return a concise comparison table or bullet summary

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