Dataify Google Local

Use this skill for Google Local/local pack keyword-and-location business results. Do not use it for map-coordinate browsing, a known Place ID, place details, or reviews.

Workflow

1. Parse the user's request into Google Local fields. Always set engine to the fixed value google_local.
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 the fields the user requested plus documented defaults only: engine: "google_local", json: "1", google_domain: "google.com", and no_cache: "false". Omit optional fields that the user did not request and that have no documented default.

python3 scripts/google_local.py --q "coffee shops" --location "New York" --gl us --hl en

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

python3 scripts/google_local.py --params-json '{"q":"coffee shops","location":"New York","gl":"us","hl":"en"}'

PowerShell may need the quotes escaped:

python3 scripts/google_local.py --params-json '{\"q\":\"coffee shops\",\"location\":\"New York\",\"gl\":\"us\",\"hl\":\"en\"}'

To let the script parse a natural-language request:

python3 scripts/google_local.py --request "搜索纽约咖啡店，语言英文，地区美国，不走缓存"

Field Mapping

Use references/google_local_api.md when exact parameter wording is needed.

Core rules:

• Always submit the API request as form data with Content-Type: application/x-www-form-urlencoded.
• Always force engine to google_local.
• Keep request values as strings unless the script accepts and normalizes a boolean.
• Omit optional fields that the user did not request unless the field has a documented default.
• Ask a follow-up only when the required search 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
• named search origin -> location
• encoded location -> uule
• page number N -> start: String((N - 1) * 10)
• Google place CID -> ludocid
• advanced search filters -> tbs
• bypass/no cache -> no_cache: "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_local.py --q "coffee shops" --location "New York" --gl us --hl en

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.