Dataify Google Shopping

When the user requests "call Google Shopping" or "shopping search/product search/price comparison", or explicitly mentions the shopping search field, the dat...

Use this skill to turn a user's Google Shopping request into a Dataify Scraper API call.

Required Pre-Call Confirmation

Before every real API call, follow this confirmation flow. These rules override any older workflow order in this skill.

1. Parse the user's request into the API body fields and fixed engine value.
2. Apply defaults only when the parameter description explicitly states a default. Do not use example YAML values, sample prompts, placeholder values, or examples such as pizza, us, en, dates, airport codes, or tokens as defaults.
3. If a required parameter has no documented default and cannot be inferred from the user request, ask for that parameter before building the table.
4. Show a Markdown table before calling the API. Do not include Authorization. Include the complete body field list from this skill's reference document, including engine, even when a field is currently blank.
5. The table must have exactly these columns: 参数名, 当前值, 默认值, 说明.
6. After the table, ask the user whether they want to modify any parameter. Do not call the API until the user explicitly confirms.
7. If the user changes a parameter, regenerate the table and ask for confirmation again.
8. If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain DATAIFY_API_TOKEN.

Use the bundled preview helper whenever possible to generate the confirmation table from this skill's reference document:

bash

python3 scripts/preview_params.py --params-json '{"q":"USER_QUERY"}'

Pass every parsed current value to preview_params.py using --params-json or matching --field value arguments. The helper reads defaults and descriptions from references/*api.md; if the helper cannot parse a default, leave the default blank rather than inventing one. 9. After confirmation and token handling, call the bundled Python script with python3 and return the API response body directly without summarizing, extracting, cleaning, translating, or reshaping it.

Workflow

1. Parse the user's request into Dataify Google Shopping fields. Use q as the shopping search query and always set engine to google_shopping.
2. If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain DATAIFY_API_TOKEN.
3. Build request parameters with only the fields the user requested plus required documented defaults. Use json: "1" and google_domain: "google.com" unless the user asks for another value. Do not use example values from the API document as defaults.
4. Before every API call, show the user a Markdown table containing the complete field list with exactly these columns: 参数名, 当前值, 默认值, 说明. Mask the token status as 已提供 or 未提供; do not display the token. Ask whether the user wants to modify the parameters and do not call the API until the user confirms.
5. If the user changes any parameter, update the values and show the complete table again before calling.
6. After confirmation, run the bundled Python script with python3. The script submits form data to the hardcoded endpoint https://scraperapi.dataify.com/request.
7. Return the script output directly to the user. Do not summarize, extract, clean, translate, or reshape the API response.

Script Usage

Run commands from this skill directory, or use the absolute path to scripts/google_shopping.py.

Preview the complete parameter table:

bash

python3 scripts/google_shopping.py --q "wireless headphones" --gl us --hl en --max_price 100 --free_shipping true --table

Call the API after the user confirms:

bash

python3 scripts/google_shopping.py --q "wireless headphones" --gl us --hl en --max_price 100 --free_shipping true

For natural-language parsing, pass the user's request:

bash

python3 scripts/google_shopping.py --request "搜索美国 Google Shopping 上 100 美元以下包邮的无线耳机，英文，返回 JSON" --table

For many fields, pass one JSON object with shell-appropriate quoting:

bash

python3 scripts/google_shopping.py --params-json '{"q":"wireless headphones","gl":"us","hl":"en","max_price":"100","free_shipping":"true"}' --table

If the user provided a token in the conversation instead of an environment variable, pass it with --token and avoid echoing it back in the final answer:

bash

python3 scripts/google_shopping.py --token "USER_TOKEN" --q "wireless headphones" --gl us --hl en

Use --dry-run only for internal verification. It prints the normalized payload JSON and does not call the API.

Field Mapping

Use references/google_shopping_api.md when you need the complete field list, defaults, or exact descriptions for the preview table.

Core rules:

• Always submit the API request as form data with Content-Type: application/x-www-form-urlencoded.
• Always force engine to google_shopping.
• Keep request values as strings unless the script accepts and normalizes a boolean.
• Omit optional fields that the user did not request unless the API document gives a real default.
• Ask a follow-up only when the required shopping query q cannot be inferred.
• If both location and uule are present, prefer the explicit uule and omit location.
• Normalize token values in the script. A token without Bearer is accepted and prefixed automatically.

Common mappings:

• "JSON" -> json: "1"
• "JSON+HTML" -> json: "2"
• "HTML" -> json: "3"
• "Light JSON" -> json: "4"
• country or region for Google behavior -> gl
• interface/search language -> hl
• page number N -> start: String((N - 1) * 10)
• raw Google Shopping filter token -> shoprs
• minimum price -> min_price
• maximum price -> max_price
• price low to high -> sort_by: "1"
• price high to low -> sort_by: "2"
• free shipping only -> free_shipping: "true"
• sale or discount items only -> on_sale: "true"
• small business items only -> small_business: "true"
• bypass cache -> no_cache: "true"