Dataify Google Finance

Search Google Finance for financial data

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

Workflow

1. Parse the user's request into Dataify Google Finance fields. Use q as the finance query and set engine to the fixed value google_finance.
2. Apply only documented defaults from the parameter descriptions:
   • engine: fixed google_finance
   • json: default 1
   • window: default 1D
   • no_cache: default false
   • q: no default; ask the user if it cannot be inferred
   • hl: no documented default; leave empty unless the user specifies it

bash

python3 scripts/google_finance.py --request "查询 NASDAQ:GOOGL，窗口 1年，英文，返回 JSON" --preview-table

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

bash

python3 scripts/google_finance.py --params-json '{"q":"NASDAQ:GOOGL","window":"1Y","hl":"en","json":"1"}' --preview-table

5. If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain DATAIFY_API_TOKEN.
6. Run the bundled Python script with python3. Run it from this skill directory, or use the absolute path to scripts/google_finance.py.

bash

python3 scripts/google_finance.py --q "NASDAQ:GOOGL" --window 1Y --hl en --json 1

For a natural-language fallback, pass the whole request:

bash

python3 scripts/google_finance.py --request "搜索苹果股票，图表范围 5天，不使用缓存"

Field Mapping

Use references/google_finance_api.md for the complete parameter descriptions and documented defaults.

Core rules:

• Always submit the API request as form data with Content-Type: application/x-www-form-urlencoded.
• Always force engine to google_finance.
• Keep request values as strings unless the script accepts and normalizes a boolean.
• Ask a follow-up only when the required finance query q cannot be inferred.
• Normalize token values in the script. A token without Bearer is accepted and prefixed automatically.
• Do not show Authorization in the pre-call parameter table.
• Do not invent defaults from examples. Only use defaults explicitly stated in the parameter descriptions.

Common mappings:

• stock, index, mutual fund, currency, or futures search term -> q
• "JSON" -> json: "1"
• "JSON+HTML" -> json: "2"
• "HTML" -> json: "3"
• "Light JSON" -> json: "4"
• interface/search language -> hl
• "1天", "1 day", or "1D" -> window: "1D"
• "5天", "5 days", or "5D" -> window: "5D"
• "1个月", "1 month", or "1M" -> window: "1M"
• "6个月", "6 months", or "6M" -> window: "6M"
• "年初至今" or "YTD" -> window: "YTD"
• "1年", "1 year", or "1Y" -> window: "1Y"
• "5年", "5 years", or "5Y" -> window: "5Y"
• "最大", "max", or "MAX" -> window: "MAX"
• bypass 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

bash

python3 scripts/google_finance.py --help

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.