openfoodfacts-guide

openfoodfacts-guide is a skill for Claude Code from cyanheads/openfoodfacts-mcp-server. It costs 99 tokens per session (1,526 once invoked), scanned A, original, Apache-2.0.

A set of rules for using Open Food Facts, a community product database containing label, ingredient, allergen, additive, nutrition, and computed food-grade information. It covers packaged foods identified by barcodes, not recalls or personal medical safety decisions.

In plain words
What is it for?
It is for checking declared allergens, ingredients, additives, nutrition, diet-related tags, Nutri-Score, NOVA, and comparisons between packaged products.
Why use it?
It helps an agent choose the right product record and communicate uncertainty when labels, barcodes, or allergen data are incomplete.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the openfoodfacts-mcp-server plugin — 35 skills, 1 MCP server shipped together

Good fit It is for checking declared allergens, ingredients, additives, nutrition, diet-related tags, Nutri-Score, NOVA, and comparisons between packaged products.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add cyanheads/openfoodfacts-mcp-server --skill openfoodfacts-guide
Clone the repo
git clone --depth 1 https://github.com/cyanheads/openfoodfacts-mcp-server

Made for: Claude Code.

Or install openfoodfacts-mcp-server, the plugin that ships this one along with the rest of its 35 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for openfoodfacts-guide

README.md
[![agentmods](https://agentmods.dev/badge/skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide/github.svg)](https://agentmods.dev/skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide)
Your own site
<a href="https://agentmods.dev/skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide"><img src="https://agentmods.dev/badge/skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for openfoodfacts-guide

Your own site · 80×15
<a href="https://agentmods.dev/skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide"><img src="https://agentmods.dev/badge/skills/cyanheads/openfoodfacts-mcp-server/openfoodfacts-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,526 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.01526
Opus 5.5 $0.00040 $0.00610
Sonnet 5.5 $0.00020 $0.00305
Haiku 4.5 $0.00010 $0.00153

Measured yesterday against content hash 04d7e385c94c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

openfoodfacts-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/openfoodfacts-guide/SKILL.md · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scope

Packaged, barcoded foods as Open Food Facts contributors recorded them: label text, declared allergens and traces, additives, Open Food Facts' computed grades, and nutrition per 100 g (per 100 ml for liquids) and per serving. It is not a verdict on whether a food is safe for a particular person, and it holds no recalls. Reference composition for generic, unbranded foods belongs to a food-composition database such as USDA FoodData Central.

Identifiers

Identifier Where it comes from
Barcode The user (a scan or the pack), or the rows of off_search_products. One product has many barcodes — sizes, regional editions, reformulations — and each is a separate record with its own completeness and grades.
Tag ID (en:organic, en:nuts) off_browse_taxonomy, or the tag arrays on a product record. The same ID can mean different things in different facets: the category en:nuts holds peanut products, while the allergen en:nuts means tree nuts.
Category tags A record carries its category's ancestors too (a pistachio row lists en:snacks, en:salty-snacks, en:nuts, en:pistachios), so a broad category filter also matches products filed under its subcategories.
Off-taxonomy entries A product's tag arrays can hold contributor entries the taxonomy never canonicalized: a non-en: prefix or display text with capitals, spaces, or accents (fr:Goûter, en:Pâtes à tartiner). Don't reuse one as a filter value; resolve the concept with off_browse_taxonomy first.

Gates

  1. Allergy questions: never answer "safe" or "free of X". Report what the record says and how far it goes. Read all three sources: ingredients_text (in the label's own language, often with allergens emphasized in capitals or brackets), allergens_tags, and traces_tags. An empty traces_tags means no trace data was entered, not that the label carries no warning. When the three disagree, say the record is unreliable: a record can carry a truncated ingredients text beside allergen tags that text cannot support. End by pointing the user to the physical label.
  2. Nut allergies need two tags. en:nuts means tree nuts; peanuts are the separate en:peanuts. Check both on the record, and pass both to exclude_allergens or exclude_traces.
  3. Free-from searches start from a positive claim. An exclusion alone also passes every product with no allergen data entered, so select first on something the record asserts: a label (en:no-gluten, en:vegan) or a free-from category (en:gluten-free-pasta). Add the exclusion on top, then confirm shortlisted barcodes with off_get_product. For vegan, the ingredients-analysis verdict en:vegan is Open Food Facts' computation from the parsed ingredients, while the label en:vegan is a claim printed on the pack. They are different evidence, so say which one you used.
  4. Grade ranges take one call per grade. nutrition_grade and nova_group each take a single value. For "Nutri-Score B or better", search once with a and once with b, then merge the results. A product with no grade drops out of both searches.
  5. A product named without a barcode: pick a barcode deliberately. Don't take the first search row on faith. Records for one product can carry different Nutri-Score and NOVA grades even when their nutrition is identical, when one record's ingredient list or other entered data is incomplete. Prefer the user's own barcode. Otherwise sort by unique_scans_n, favor high completeness, and name the barcode the answer came from.
  6. Grades are Open Food Facts' computation from the record, not the grade printed on the pack. When a user quotes a different grade, the record's data is the first suspect: check its completeness, data_quality_tags, and ingredient list.
  7. Spend searches one at a time. The search budget is about 10 upstream requests a minute on the default configuration. The server process holds it, so every caller of a shared deployment draws from it, and each retry of a failing request spends its own slot. Never fan out parallel searches; when the budget runs out, the error's data.retryAfter gives the wait. Product lookups draw on a separate budget, but off_compare_products spends one lookup from it per barcode, the same as off_get_product.

Read the full file on GitHub · 42 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 42 lines · 99 tokens per session scan A 04d7e385c94c

Subscribe to this mod's changes

openfoodfacts-guide is a skill published in the GitHub repository cyanheads/openfoodfacts-mcp-server (1 stars, last pushed 2d ago), licensed Apache-2.0. It adds 99 tokens to every session and 1,526 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-28.

Related

Other skills, from other repositories

open-meteo-guide

Tool choice, gates, and workflows for the openmeteo weather tools, covering threshold odds from the ensemble, frost, anomalies against a normal, 2050 projections, surf spots, river flood outlooks, and air quality for a set hour. Use before answering a weather, climate, marine, river, or air-quality question from…

cyanheads/open-meteo-mcp-server · 103 tokens

ensembl-guide

Gates and identifier chains for the ensembl tools. Covers checking a coordinate's assembly before you pass it in, finding a gene's counterpart in another species through homology, reading multi-allelic and capped VEP results, and which Ensembl object holds the UniProt, RefSeq, GO, and PDB references. Use when an…

cyanheads/ensembl-mcp-server · 95 tokens

noaa-spaceweather-guide

Judgment for the noaaspaceweather tools — turning SWPC Kp, storm scales, solar wind, flares, and alerts into answers about aurora visibility tonight, coming geomagnetic storms, radio blackouts, and impacts on HF radio, GPS, satellites, and power grids. Use before answering an aurora or space-weather question with…

cyanheads/noaa-spaceweather-mcp-server · 101 tokens

noaa-marine-guide

Gates and conventions for the noaamarine tools (NOAA CO-OPS tides, tidal currents, water levels; NDBC buoys). Covers which station serves which tool, why a place-name search misses, time-zone and direction conventions across the two sources, and what the server cannot answer (forecasts, warnings, past buoy readings).…

cyanheads/noaa-marine-mcp-server · 106 tokens

usgs-water-guide

Gates and workflows for the water tools over USGS stream gages and groundwater wells. Covers whether a river or aquifer is high or low right now, telling live gages from discontinued ones, reading depth-to-water rankings (they run inverted), finding the parameter code a site actually reports, time zones and data lag…

cyanheads/usgs-water-mcp-server · 99 tokens

omh-geospatial-analysis

This is an OMH geospatial-analysis workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

rlaope/oh-my-hermes · 57 tokens