Methodology
Our data methodology
How the 200 skills in this library are built, what data sits behind them, how they are reviewed, and what they deliberately will not do.
Key data
FoodSkills.ai builds each of its 200 free AI skills through a 5-stage process: define a recurring CPG job, author a model-agnostic prompt with a fixed input and output contract, add guardrails that forbid invented statistics, test it against realistic briefs in ChatGPT, Claude and Gemini, then review and publish it with a visible last-updated date. Reviewed by the Tastewise F&B analyst team. Updated August 13, 2026.
- Skills published
- 200
- Build stages
- 5
- Roles covered
- 7
- Models tested
- 3
Updated
Reviewed by CPG & food retail analysts
Written and reviewed by the Tastewise F&B analyst team. Every skill is tested against real CPG briefs before publication — see our data methodology.
How a skill gets built, in 5 stages
| Stage | What happens | Output |
|---|---|---|
| 1. Job definition | Pick a recurring CPG job (line review, sell-in story, claims pass) and write down the inputs, the decision it feeds and the artefact it produces. | A named job-to-be-done |
| 2. Prompt authoring | Write a model-agnostic prompt with an explicit role, a fixed input contract of bracketed placeholders, and a fixed output structure so two runs are comparable. | prompt.md |
| 3. Guardrails | Add rules that forbid invented statistics and market sizes, require assumptions to be labelled, and flag regulated claims for legal review. | Rules section in every prompt |
| 4. Test against real briefs | Run the prompt on realistic category, consumer and retailer inputs in ChatGPT, Claude and Gemini, and check the output is decision-ready — not generic. | Worked example on every skill page |
| 5. Review & publish | An F&B analyst reviews the prompt and the worked example, then it ships with a visible last-updated date in all three formats. | Published skill + dated page |
Where the food & beverage expertise comes from
FoodSkills.ai is published by Tastewise. Tastewise is the AI platform built for food & beverage, trained on trillions of real-time F&B signals across menus, recipes, social, delivery and eRetail. That domain knowledge is what shapes the structure of each prompt: which fields a category review actually needs, what a buyer expects in a sell-in story, how a concept gets screened.
What the prompts do not do
- They do not invent data. Every prompt carries an explicit rule against fabricating statistics or market sizes, and requires demand signals to be labelled as assumptions to validate.
- They do not replace regulatory review. Claims, on-pack copy and nutrition language are flagged for legal and regulatory sign-off in your market.
- They are not professional advice. The output is a structured first draft that a human owns, edits and stands behind.
How updates work
Every skill page shows a visible Updated date and mirrors it as dateModifiedin that page's structured data, so you can always tell how current a skill is. The library currently holds 200 skills and was last updated July 12, 2026.
Methodology FAQ
- Where does the food & beverage context come from?
- The skills are authored by Tastewise, the AI platform built for food & beverage. The prompts encode how CPG teams actually structure innovation briefs, category reviews, sell-in stories and claims work. The prompts themselves do not contain market data — they instruct the model to work from the context you supply, and they explicitly forbid inventing statistics.
- Do the skills generate market statistics?
- No, and that is deliberate. Every prompt includes a rule against inventing statistics or market sizes, and requires any demand signal to be labelled as an assumption to validate. If you need real numbers, pair the skill with a live data source such as Tastewise.
- How often are the skills updated?
- Each skill page publishes its own last-updated date and mirrors it as dateModified in the page's structured data. The library currently holds 200 skills and was last updated July 12, 2026. Skills are revised when the underlying job changes or when testing shows a prompt drifting.
- Who reviews the skills?
- Skills are written and reviewed by F&B analysts at Tastewise before publication. Each skill is tested against realistic CPG inputs across ChatGPT, Claude and Gemini, and the worked example on the page is real output from that testing.
- What are the limits of these skills?
- They produce a structured first draft, not a finished deliverable and not professional advice. Outputs need a human pass for accuracy, brand voice and regulatory compliance — on-pack and marketing claims in particular must go through your own legal and regulatory review.
See the skills the method produces
200 free AI skills for food & beverage teams, each with a worked example and a published update date.