Dataify Google Flights
/install dataify-google-flights
Dataify Google Flights
Use this skill to turn a user's Google Flights request into a Dataify Scraper API form POST.
Required Pre-Call Confirmation
Before every real API call, follow this confirmation flow. These rules override any older workflow order in this skill.
- Parse the user's request into the API body fields and fixed
enginevalue. - 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. - If a required parameter has no documented default and cannot be inferred from the user request, ask for that parameter before building the table.
- Show a Markdown table before calling the API. Do not include
Authorization. Include the complete body field list from this skill's reference document, includingengine, even when a field is currently blank. - The table must have exactly these columns:
参数名,当前值,默认值,说明. - After the table, ask the user whether they want to modify any parameter. Do not call the API until the user explicitly confirms.
- If the user changes a parameter, regenerate the table and ask for confirmation again.
- 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:
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
- Parse the user's request into Dataify Google Flights fields. Read
references/google_flights_api.mdfor the full field list, accepted values, defaults, and conditional requirements. - Before every API call, run the script in dry-run Markdown mode and show the user the complete request parameter table. Then ask whether they want to modify anything. Do not call the API until the user confirms.
- Do not show
Authorization. - Show the complete documented body field list, not only fields present in the user request.
- Use exactly these columns:
参数名,当前值,默认值,说明. - For parameters whose description states a default value, use that default when the user did not specify a value.
- Leave default value blank when the parameter description does not state a default.
- Never use examples, placeholders, sample YAML values, or blank values as defaults.
- Do not show
- If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain
DATAIFY_API_TOKEN. - Build request parameters with documented defaults only. The script submits these parameters as form data, not a JSON request body.
- After the user confirms the table, run the bundled Python script with
python3. Run it from this skill directory, or use the absolute path toscripts/google_flights.py.
python3 scripts/google_flights.py --params-json '{"departure_id":"JFK","arrival_id":"LAX","type":"2","outbound_date":"2026-06-01","currency":"USD","gl":"us","hl":"en"}' --dry-run --dry-run-format markdown
If the user confirms and provided a token in the conversation instead of an environment variable, pass it with --token and never echo it back:
python3 scripts/google_flights.py --token "USER_TOKEN" --params-json '{"departure_id":"JFK","arrival_id":"LAX","type":"2","outbound_date":"2026-06-01"}'
- Return the script output directly to the user. Do not summarize, extract, clean, translate, or reshape the API response body.
Mapping Rules
- Always submit the API request as form data with UTF-8 encoding and
Content-Type: application/x-www-form-urlencoded. - Always force
enginetogoogle_flights. - Use
json: "1"unless the user asks for another output format. - Resolve relative dates from the conversation date, then pass dates as
YYYY-MM-DD. - Ask a follow-up when the user's route or requested continuation cannot be inferred safely. Do not require dates unless the user explicitly asks for a dated itinerary.
- If the user gives city names instead of airport codes and the airport is ambiguous, ask for the airport code or Google kgmid.
- Normalize token values in the script. A token without
Beareris accepted and prefixed automatically.
Common mappings:
- "JSON" ->
json: "1" - "JSON+HTML" ->
json: "2" - "HTML" ->
json: "3" - "Light JSON" ->
json: "4" - one-way/single trip ->
type: "2" - round trip/return trip ->
type: "1" - multi-city ->
type: "3"andmulti_city_json - economy/premium economy/business/first ->
travel_class: "1","2","3","4" - best/price/departure time/arrival time/duration/emissions sort ->
sort_by: "1","2","3","4","5","6" - any stops/nonstop/one stop or fewer/two stops or fewer ->
stops: "0","1","2","3" - bypass cache/no cache ->
no_cache: "true" - deep search ->
deep_search: "true"
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install dataify-google-flights - 安装完成后,直接呼叫该 Skill 的名称或使用
/dataify-google-flights触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Dataify Google Flights 是什么?
When the user requests "calling Google Flights" or "searching for flight prices/itineraries", or explicitly mentions the flight query field, the dataify-goog... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 39 次。
如何安装 Dataify Google Flights?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install dataify-google-flights」即可一键安装,无需额外配置。
Dataify Google Flights 是免费的吗?
是的,Dataify Google Flights 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Dataify Google Flights 支持哪些平台?
Dataify Google Flights 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Dataify Google Flights?
由 dataify-server(@dataify-server)开发并维护,当前版本 v1.0.0。