Dataify Google Flights

Use this skill to turn a user's Google Flights request into a Dataify Scraper API form POST.

Workflow

1. Parse the user's request into Dataify Google Flights fields. Read references/google_flights_api.md for the full field list, accepted values, defaults, and conditional requirements.
   • 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.
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 documented defaults only. The script submits these parameters as form data, not a JSON request body.
4. After the user confirms the table, run the bundled Python script with python3. Run it from this skill directory, or use the absolute path to scripts/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

Mapping Rules

• Always submit the API request as form data with UTF-8 encoding and Content-Type: application/x-www-form-urlencoded.
• Always force engine to google_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 Bearer is 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" and multi_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"

Result presentation

• Return a compact, user-facing result by default: the most relevant titles, links, and vertical-specific fields, plus a count or truncation note when useful.
• Do not expose transport details, fixed engine fields, task plumbing, or the full response envelope in the ordinary flow.
• Return raw JSON or HTML only when the user explicitly requests raw output.
• Preserve source links and distinguish missing fields from empty values; do not invent data.

Quick Start

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

Parameter interaction policy

• For a clear, low-risk, read-only, and low-cost request, apply safe defaults and execute immediately. A short execution summary is optional; do not pause for confirmation.
• Ask only for a missing required input, a material ambiguity, a high-volume or multi-page scope, a media download, a choice that materially changes credit usage, an irreversible action, or an explicit user request to review parameters.
• When confirmation is required, show only user-facing values that affect the target, scope, output, or cost. Prefer one concise sentence; use a compact table only when three or more consequential values are easier to compare.
• Never show fixed fields, empty optional fields, unchanged defaults, credentials, or internal implementation parameters such as engine selectors, response-format flags, offsets, spider IDs, and file-name templates.
• Keep advanced filters hidden unless the user asks for them or they are needed to resolve ambiguity. Never substitute documentation example values for missing required user input.
• After returning results, offer relevant refinements instead of forcing all optional decisions before the first result.

Account CTA policy

• Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
• For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts receive 50 free credits. Never ask the user to paste the token into chat.
• Detect the current operating system and shell. Show only the matching session-scoped setup command first (export for macOS/Linux shells, $env: for Windows PowerShell, or set for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
• After the user says the token is configured, verify only whether DATAIFY_API_TOKEN is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
• Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project .env unless the execution path explicitly loads it, and ensure .env is ignored by version control.
• For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.
• During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.