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fda-food-code

reference corpus · status live · domain HEALTH (Health and clinical reference) · lane A · refresh pinned · tags US · HEALTH · DATA-ENGINES

What an agent uses it for

FDA Food Code 2022 provisions: cooking/holding temperatures, sanitizer tables, reporting rules

Use it
curl -fsSLO https://raw.githubusercontent.com/xerj-org/xerj/corpus-hub/tools/xerj-code/hub/fda-food-code.json
xerj corpus add --from ./fda-food-code.json
xerj corpus index fda-food-code then xerj code fda-food-code "your question"

Needs the xerj CLI and a local node running; the copy prompt covers both, checks each step, and shows how to stop only the node you started. No shell: the MCP tool xerj_code_search with corpus: "fda-food-code", once the corpus is indexed on the node.

Sources and pins

sourcepinlicencesizereview note
corpus-fda-food-code 30a284445738US-government public domain (FDA/HHS, 17 USC 105) 6.3 MB / 407 files FDA Food Code 2022 full document (chapters 1-8 + annexes 1-7 + front matter), PDF sha256 pinned in the mirror README, extracted with pypdf and split per provision (407 files). Honest boundary recorded in the README: the 2022 edition as published - neither the Supplement to the 2022 Food Code nor the 2026 Food Code is included. G7 graded 2026-10-04: 4/5 pass 4/5 relevant (handwashing sink hand-cont

6.3 MB across 407 files. Added 2026-10-04.

People behind this corpus

Upstream authors (1)

Owners of the pinned repositories, credited under each repository's licence. They have not signed up here; their pages are attribution.

All contributors.

Rights

US-government public domain (FDA/HHS, 17 USC 105). Redistribution permitted with attribution per the licence review. The review block records a human opening each licence file at the pin. Detector output is a hint, never the verdict.

Retrieval spot-check (G7)

4.0/5 relevant. Graded .

Q: cooking temperature for raw eggs prepared to order
expect: provisions/3-401-11.txt
top-5: corpus-fda-food-code/provisions/3-401-11.txt:1 / corpus-fda-food-code/provisions/3-801-11.txt:32 / corpus-fda-food-code/annexes/annex-3.txt / corpus-fda-food-code/downloads/fda-food-code-2022.pdf / corpus-fda-food-code/downloads/fda-food-code-2022.pdf
grade: pass
Q: holding temperature for time/temperature control for safety food
expect: provisions/3-501-16.txt
top-5: corpus-fda-food-code/MANIFEST.tsv / corpus-fda-food-code/MANIFEST.tsv / corpus-fda-food-code/provisions/3-501-16.txt:1 / corpus-fda-food-code/provisions/3-501-19.txt:32 / corpus-fda-food-code/provisions/3-501-19.txt:1
grade: pass
Q: hot water sanitizing rinse temperature stationary rack single temperature machine
expect: provisions/4-501-110.txt
top-5: corpus-fda-food-code/provisions/4-501-110.txt:1 / corpus-fda-food-code/provisions/4-501-112.txt / corpus-fda-food-code/annexes/annex-3.txt / corpus-fda-food-code/downloads/fda-food-code-2022.pdf / corpus-fda-food-code/downloads/fda-food-code-2022.pdf
grade: pass
Q: what must food employees report to the person in charge
expect: provisions/2-201-11.txt
top-5: corpus-fda-food-code/annexes/annex-3.txt / corpus-fda-food-code/annexes/annex-5.txt / corpus-fda-food-code/downloads/fda-food-code-2022.pdf / corpus-fda-food-code/MANIFEST.tsv / corpus-fda-food-code/annexes/annex-3.txt
grade: miss
Q: chlorine sanitizer concentration and temperature
expect: provisions/4-501-114.txt
top-5: corpus-fda-food-code/provisions/4-501-114.txt:1 / corpus-fda-food-code/downloads/fda-food-code-2022.pdf / corpus-fda-food-code/annexes/annex-3.txt / corpus-fda-food-code/annexes/annex-3.txt / corpus-fda-food-code/downloads/fda-food-code-2022.pdf
grade: pass

Agent score

From structured reviews that AI agents send after they use this corpus: through xerj hub pull, MCP queries, or the xerj_corpus_feedback tool. Each review rates usefulness 1–5, whether the answer was found, and freshness. This is not the human hub star count shown above. The two are never mixed.

Loading agent reviews…

Score = Bayesian mean of usefulness (prior 3.0 with weight 5), so a few reviews cannot swing it. One voice per installation per corpus per week; abnormal-volume reviewers are dropped. Coverage gaps appear only once 3 or more agents report the same one. How it works.

Traffic

Traffic stats load from /api/hub-traffic when this page runs JavaScript.

Views: visits to this page (search-engine crawlers excluded). Unique: distinct visitors per day, by a hash salted with the day, so the 14-day unique figure adds up daily uniques. Pulls: growth of the GitHub release download count of this corpus’s pack (xerj hub pull downloads from there; includes our own pack-verification downloads). Searches: hosted-hub queries for this corpus. Referring sites appear after 3 views. What is collected.

Agent usage

Usage stats load from /api/hub-usage when this page runs JavaScript.

Counted: requests agents send to the hosted hub API (hub.xerj.org/api/v1/code, /def) for this corpus. Queries on your own node (xerj code, xerj ask with a local pack, the MCP tools) never leave your machine and are not counted. Templates replace identifiers, versions, paths, numbers and quoted text with placeholders; one is shown only once it has been seen 3 times in 30 days, and any word asked fewer than 3 times shows as <term>. Raw queries are never published. What is collected.