dietary-assessment
Methods for assessing what people actually eat — 24-hour recall, food frequency questionnaires, diet diaries, biomarkers, duplicate-plate studies, and controlled feeding. Covers the relative strengths and biases of each instrument, how to choose among them for a given question, and how to interpret results in the presence of measurement error. Use when a user wants to estimate population-level intake, individual-level intake, or evaluate the plausibility of a dietary claim that depends on how intake was measured.
npx skills add majiayu000/claude-skill-registry --skill dietary-assessment --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Dietary Assessment "What do people actually eat?" is harder to answer than it looks. Every large claim about diet and health depends on answering it for thousands of people over months or years, and every instrument that attempts to do so has known biases. This skill catalogs the common instruments, documents the biases each one introduces, and gives heuristics for choosing the right tool for a question and reading the resulting numbers with appropriate skepticism. **Agent affinity:** lind (controlled-trial design), ancel-keys (population-scale dietary assessment) **Concept IDs:** nutrition-assessment-methods, nutrition-study-design, nutrition-measurement-error ## The instrument menu ### 24-hour dietary recall **What it is.** A trained interviewer walks the participant through everything eaten and drunk in the previous 24 hours, prompting with portion-size aids and a multi-pass protocol (quick list, meal structure, forgotten-foods probe, detail pass, final review). The USDA Automated Multiple-Pass Method is the reference implementation. **Strengths.** Open-ended; captures foods not on any predefined list. Short-term memory is more accurate than long-term. With multiple non-consec
- The instrument menu
- 24-hour dietary recall
- Food frequency questionnaire (FFQ)
- Weighed food diary
- Duplicate-plate study
- Biomarkers of intake
- Controlled feeding study
- Choosing an instrument — decision protocol
- Step 1 — What is the question?
- Step 2 — What is the target measurement accuracy?
- Step 3 — Will the population comply?
- Worked example — reading an FFQ-based relative-risk claim
- Worked example — an FFQ-vs-biomarker discrepancy
- Assessment protocol for a "what should I eat" question
What does the dietary-assessment skill do?
Methods for assessing what people actually eat — 24-hour recall, food frequency questionnaires, diet diaries, biomarkers, duplicate-plate studies, and controlled feeding. Covers the relative strengths and biases of each instrument, how to choose among them for a given question, and how to interpret results in the presence of measurement error. Use when a user wants to estimate population-level intake, individual-level intake, or evaluate the plausibility of a dietary claim that depends on how intake was measured.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dietary-assessment --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.