Dataify Google Videos

Search Google Videos

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

Workflow

1. Parse the user's request into Google Videos fields. Use q as the video search query and force engine to google_videos.
2. Build request parameters with the fields the user requested plus the documented defaults only: json: "1", google_domain: "google.com", no_cache: "false", nfpr: "0", and filter: "0". Do not treat examples such as us, en, or true as defaults.
3. If the user requests changes, update the parameters and show the complete table again. Call the API only after the user confirms.
4. If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain DATAIFY_API_TOKEN.
5. Run the bundled Python script with python3. Run it from this skill directory, or use the absolute path to scripts/google_videos.py.

bash

python3 scripts/google_videos.py --request "search Google videos for electric cars in English" --preview-table

bash

python3 scripts/google_videos.py --q "electric cars" --hl en

For many fields, pass one JSON object with shell-appropriate quoting. The script will still submit form data to the API:

bash

python3 scripts/google_videos.py --params-json '{"q":"electric cars","json":"1","google_domain":"google.com","gl":"us","hl":"en","no_cache":"true"}'

Field Mapping

Use references/google_videos_api.md when you need the exact field list, defaults, constraints, or table descriptions.

Core rules:

• Always submit the API request as form data with Content-Type: application/x-www-form-urlencoded.
• Always force engine to google_videos.
• Use UTF-8 for script source, form encoding, and displayed text.
• Keep request values as strings unless the script accepts and normalizes a boolean.
• Ask a follow-up only when the required video query q cannot be inferred.
• If uule is present, 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"
• Google domain -> google_domain
• country or region for Google behavior -> gl
• interface/search language -> hl
• named search origin -> location
• Google encoded location -> uule
• page number N -> start: String((N - 1) * 10)
• advanced video filters, duration, quality, source, or date -> tbs
• bypass cache / no cache -> no_cache: "true"
• language-restricted results -> lr, formatted like lang_fr
• safe search on/off -> safe: "active" or safe: "off"
• exclude autocorrected query results -> nfpr: "1"
• include autocorrected query results -> nfpr: "0"
• disable similar/omitted result filters -> filter: "1"
• enable similar/omitted result filters -> filter: "0"

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_videos.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.