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nutrition-provider-r2营养提供者 r2

Agent Skill

nutrition-provider-r2 用于处理浏览器自动化、网页检查和页面信息提取,适合在 OpenClaw 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nutrition-provider-r2(营养提供者 r2)
来源仓库:https://github.com/snailb1007/nutrition-provider-r2
安装命令:
openclaw skills install nutrition-provider-r2
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install nutrition-provider-r2

简介

nutrition-provider-r2 抓取越南营养供应商信息并存入 Cloudflare R2。

  • 使用 scrapling-ficial 逐页爬取原始数据。
  • 适合供应链管理与供应商数据库建设。nutrition-provider-r2 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装前需配置 R2 存储桶与 API 凭证。
  • 适用于研究检索类任务中的数据整理与归档需求。

SKILL.md

name
nutrition-provider-r2
description
crawl the Vietnam nutrition provider page-by-page with scrapling-official and upload each raw provider record to Cloudflare R2 after fetch. use for provider-specific ingestion where the canonical data comes from the provider's foods or prepared-dish JSON APIs, records from one page may upload in parallel with stable object keys, and each page must still respect a minimum 60 second crawl-plus-upload window before the next page begins.
license
MIT-0
metadata
{ "openclaw": { "emoji": "🥗", "homepage": "https://viendinhduong.vn/vi/cong-cu-va-tien-ich/gia-tri-dinh-duong-thuc-pham", "requires": { "bins": ["uv"] }, "install": [{ "id": "uv-brew", "kind": "brew", "formula": "uv", "bins": ["uv"], "label": "Install uv (brew)" }] } }

Nutrition Provider R2

This skill is a provider-specific orchestration wrapper around scrapling-official.

Its job is to take the payload that scrapling-official fetched, split each canonical page into individual provider records, and upload those records to Cloudflare R2.

It does not replace scrapling-official as the crawler.

Use it when the target is one of the Vietnam nutritional portal lookup listings and the job is:

  • crawl page-by-page
  • preserve each provider record in raw form
  • upload the records from each page to Cloudflare R2 immediately after that page is fetched

Do not normalize provider records into a custom nutrition schema. Preserve provider fields, response bodies, pagination clues, and raw linked payloads exactly as obtained whenever possible.

Required skill

This skill depends on scrapling-official for crawling.

  • If scrapling-official is not installed or not set up yet, stop and tell the user to install and configure that skill first.
  • Let scrapling-official own crawl execution, endpoint discovery, rendering mode, and fetch escalation.
  • Follow scrapling-official's fetch escalation strategy exactly: start with get, then move to fetch if needed, then stealthy-fetch only when the earlier modes fail or protection requires it.
  • Do not fall back to a different crawler or browser stack when scrapling-official is missing.

Workflow

  1. Read {baseDir}/references/source-notes.md for the default source URL, pagination clues, and stop conditions.
  2. Confirm the R2 credentials are present:

- R2_ACCOUNT_ID - R2_ACCESS_KEY_ID - R2_SECRET_ACCESS_KEY - R2_BUCKET

  1. Ask scrapling-official to inspect the provider page and determine which payload actually contains the canonical records for the current request.
  2. For this provider, prefer the canonical JSON payload when scrapling-official discovers it, instead of the outer HTML shell.
  3. Current observed provider behavior:

- food lookup page gia-tri-dinh-duong-thuc-pham exposes records from GET /api/fe/foodNatunal/getPageFoodData - prepared-dish lookup page gia-tri-dinh-duong-mon-an exposes records from GET /api/fe/tool/getPageFoodData - default params observed on page load: - foods: page=1&pageSize=15&energy=0 - prepared dishes: page=1&pageSize=15 - observed filter params: - foods: name, category, energy - prepared dishes: at least name, energy, with additional filters visible in the UI such as group and region; let scrapling-official discover the exact live request params

  1. Treat the start of each page fetch as the start time for that page's pacing window.
  2. Save the raw payload that scrapling-official fetched for that page without normalizing item fields.
  3. If scrapling-official can fetch the canonical JSON payload, treat raw.data as the list of provider records for that page.
  4. Split that page payload into one record object per item in data.
  5. Upload each record object as its own R2 object.
  6. Record uploads from the same page may run in parallel, but every record object must use a stable object key so reruns do not create duplicates.
  7. Prefer a provider-stable identifier for the key:

- _id first - then code - only use another deterministic identifier if neither exists

  1. Prefer letting the helper split and upload records directly from the page payload:

- uv run {baseDir}/scripts/upload_page_to_r2.py --extract-foods --page-index <n> --skip-existing

  1. The helper flag name --extract-foods is retained for compatibility, but it may also be used for prepared-dish page payloads because both current source types return data arrays.
  2. If the agent already split records outside the helper, it may still upload one item at a time with --food-id.
  3. Only capture the outer HTML page as a fallback debugging artifact when scrapling-official cannot reach the canonical payload directly. Do not upload the HTML shell as the primary dataset.
  4. Wait for all record uploads from the current page to finish.
  5. Measure total time for the page as:

- page fetch start - plus record extraction - plus all record uploads

  1. If the total time for the current page is less than 60 seconds, wait the remaining time before starting the next page.
  2. Let scrapling-official handle the actual pagination requests.
  3. Use the provider payload itself to decide when to stop:

- keep paginating while the canonical payload remains non-empty - stop when the provider indicates no more rows - stop if a next request repeats data already seen

  1. Never start the next page before the current page has both:

- finished all uploads - satisfied the 60 second minimum page window

Operating Rules

  • Preserve provider data as-is. Do not rewrite field names, flatten structures, or infer a nutrition schema.
  • Allow lightweight wrapper metadata only outside the raw payload, such as source_url, fetched_at, page_index, content_type, and storage_key.
  • Upload one object per provider record, not one object for the whole page payload.
  • Stop naturally when pagination ends. Do not invent more pages.
  • scrapling-official is responsible for extracting or fetching the correct provider payload.
  • Prefer the provider JSON API response over rendered HTML whenever scrapling-official can access both.
  • Do not store the page shell HTML as the primary page payload when the JSON payload already contains the canonical rows and nutrition arrays.
  • Record uploads from the same page may be concurrent.
  • Use stable R2 object keys so duplicate runs overwrite or skip the same object instead of creating duplicates.
  • Finish all record uploads for the current page before page N+1 begins.
  • Enforce a minimum 60 second crawl-plus-upload window per page to avoid overloading the provider.
  • If scrapling-official fetches JSON from an XHR endpoint, store that JSON body unchanged.
  • If HTML is captured for debugging, store it separately from the canonical payload and do not treat it as the canonical dataset.
  • If a page fails, retry briefly. If it still fails, upload a failure record only when the caller explicitly wants failure capture.

Concurrency

Use page-sequential crawling with record-level upload concurrency.

  • Exactly one page in flight at a time.
  • Records from the same page may upload in parallel.
  • Do not start page N+1 until page N has finished all uploads.
  • Enforce a minimum total duration of 60 seconds for each page, measured from the start of fetch to the completion of all uploads and any required remaining wait.

R2 Settings

Required environment variables:

  • R2_ACCOUNT_ID
  • R2_ACCESS_KEY_ID
  • R2_SECRET_ACCESS_KEY
  • R2_BUCKET

Optional environment variables used by the helper when --key is not passed:

  • R2_PREFIX default raw
  • SOURCE_NAME default nutrition-provider
  • RUN_ID default current UTC timestamp in YYYY-MM-DDTHH-MM-SSZ

When supporting both provider sources, do not reuse the same storage namespace for both in the same crawl run.

  • prefer SOURCE_NAME=viendinhduong-foods for gia-tri-dinh-duong-thuc-pham
  • prefer SOURCE_NAME=viendinhduong-dishes for gia-tri-dinh-duong-mon-an
  • or pass --source-name explicitly per crawl job

Recommended Output Shape

Wrap the provider payload with minimal crawl metadata only when needed for storage traceability:

{
  "source_url": "https://viendinhduong.vn/api/fe/foodNatunal/getPageFoodData?page=1&pageSize=15&energy=0",
  "page_index": 1,
  "fetched_at": "2026-03-15T10:00:00Z",
  "content_type": "application/json",
  "raw": {
    "data": [],
    "current_page": 1,
    "per_page": 15,
    "total": 853
  }
}

The foods endpoint currently returns page-level JSON with top-level keys data, current_page, per_page, and total. Each food item currently includes _id, code, name_vi, name_en, category, categoryEn, nutrition, and energy.

The prepared-dish endpoint currently returns page-level JSON with top-level keys current_page, data, first_page_url, from, last_page, last_page_url, links, next_page_url, path, per_page, prev_page_url, to, and total. Each dish item currently includes _id, category_id, code, description, dish_components, food_area_id, image, name_vi, name_en, nutritional_components, total_energy, category_name, category_name_en, and category_description.

Use those richer raw objects only as the source page payloads to split into per-record uploads.

Recommended per-record upload shape:

{
  "source_url": "https://viendinhduong.vn/api/fe/foodNatunal/getPageFoodData?page=1&pageSize=15&energy=0",
  "page_index": 1,
  "fetched_at": "2026-03-15T10:00:00Z",
  "content_type": "application/json",
  "raw": {
    "_id": "6877a6b660d6c84e9bd5cca4",
    "code": "10001",
    "name_vi": "Sữa bò tươi",
    "name_en": "Milk cow, fresh (Fluid)",
    "category": "Sữa và sản phẩm chế biến",
    "categoryEn": "Milk and processed products",
    "nutrition": [],
    "energy": 74
  }
}

Upload Helper

Use uv run {baseDir}/scripts/upload_page_to_r2.py.

The helper supports two modes:

  • explicit key mode with --key
  • generated key mode from R2_PREFIX, SOURCE_NAME, RUN_ID, --page-index, and optional --food-id

Generated keys follow this layout:

  • record payload success: raw/<source>/<run_id>/page-0001/food-6877a6b660d6c84e9bd5cca4.json
  • debug or failure artifact: raw/<source>/<run_id>/failures/page-0001.json

For this skill, per-record upload is the default and expected mode.

  • prefer --extract-foods when the input is a full canonical page JSON payload from either supported source
  • pass a stable --food-id only when uploading a single already-split record object
  • prefer --skip-existing when reruns are possible
  • do not upload a whole canonical page as one object unless you are intentionally storing a debug or failure artifact

Examples:

uv run {baseDir}/scripts/upload_page_to_r2.py \
  --input tmp/page-0001.json \
  --page-index 1 \
  --extract-foods \
  --skip-existing
uv run {baseDir}/scripts/upload_page_to_r2.py \
  --input tmp/food-10001.json \
  --page-index 1 \
  --food-id 6877a6b660d6c84e9bd5cca4 \
  --skip-existing
cat tmp/food-10001.json | uv run {baseDir}/scripts/upload_page_to_r2.py \
  --page-index 1 \
  --food-id 10001 \
  --skip-existing \
  --content-type application/json
uv run {baseDir}/scripts/upload_page_to_r2.py \
  --input tmp/food-10001.json \
  --key raw/viendinhduong/2026-03-15T10-00-00Z/page-0001/food-10001.json

Only for debug or failure capture:

uv run {baseDir}/scripts/upload_page_to_r2.py \
  --input tmp/page-0001.json \
  --page-index 1 \
  --failed

Source Notes

For this provider target, use {baseDir}/references/source-notes.md.

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