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dataify-server

Dataify Google Videos

by dataify-server · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install dataify-google-videos
Description
When the user requests "Call Google Videos" or "Video Search", or explicitly mentions the video field, the dataify-google-videos skill is triggered.
README (SKILL.md)

Dataify Google Videos

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

Required Pre-Call Confirmation

Before every real API call, follow this confirmation flow. These rules override any older workflow order in this skill.

  1. Parse the user's request into the API body fields and fixed engine value.
  2. 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.
  3. If a required parameter has no documented default and cannot be inferred from the user request, ask for that parameter before building the table.
  4. Show a Markdown table before calling the API. Do not include Authorization. Include the complete body field list from this skill's reference document, including engine, even when a field is currently blank.
  5. The table must have exactly these columns: 参数名, 当前值, 默认值, 说明.
  6. After the table, ask the user whether they want to modify any parameter. Do not call the API until the user explicitly confirms.
  7. If the user changes a parameter, regenerate the table and ask for confirmation again.
  8. 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

  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. Before every API call, show the complete parameter table to the user and ask whether they want to modify anything. The table must contain only these columns: parameter name, current value, default value, and description. Include the complete field list from references/google_videos_api.md, including Authorization and engine. Mask any token value, or show missing when no token is available.
  4. If the user requests changes, update the parameters and show the complete table again. Call the API only after the user confirms.
  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_videos.py.

Preview the confirmation table:

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

Call the API after confirmation:

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

If the user provided a token in the conversation instead of an environment variable, pass it with --token and avoid echoing it back in the final answer:

python3 scripts/google_videos.py --token "USER_TOKEN" --q "electric cars" --gl us --hl en

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

python3 scripts/google_videos.py --params-json '{"q":"electric cars","json":"1","google_domain":"google.com","gl":"us","hl":"en","no_cache":"true"}'
  1. Return the script output directly to the user. Do not summarize, extract, clean, translate, or reshape the API response.

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"
Usage Guidance
Install only if you trust OOMOL and are comfortable granting the connected account access to your Airtable data. Review Airtable scopes, and require explicit confirmation before allowing create, update, or delete actions.
Capability Assessment
Purpose & Capability
The skill is explicitly for Airtable access and supports listing bases, reading schemas and records, and creating, updating, or deleting records; those capabilities match the stated purpose but can affect real Airtable data.
Instruction Scope
Instructions are scoped to `oo connector` Airtable actions, require fetching the live schema before running actions, and direct explicit user confirmation for write or destructive operations.
Install Mechanism
The artifact is markdown-only and allows `Bash(oo *)`; it depends on the separately installed and authenticated OOMOL CLI rather than bundling executable code.
Credentials
Use of Airtable credentials through an OOMOL-connected account is proportionate for this integration, but users should ensure the connected Airtable token is appropriately scoped.
Persistence & Privilege
No background workers, persistence hooks, local credential scraping, privilege escalation, or hidden long-running behavior are evident in the reviewed artifacts.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install dataify-google-videos
  3. After installation, invoke the skill by name or use /dataify-google-videos
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of dataify-google-videos. - Transforms Google Videos search requests into Dataify Scraper API form submissions. - Introduces a step-by-step pre-call confirmation flow with a mandatory Markdown table, requiring user confirmation before all API calls. - Implements strict parameter handling: only documented defaults, no invented or example-based values. - Handles session token requirements, instructing users to sign in if missing. - Leverages a bundled Python helper and preview tool to display and update parameter tables. - Directly returns Dataify response data without additional processing or summarization.
Metadata
Slug dataify-google-videos
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Dataify Google Videos?

When the user requests "Call Google Videos" or "Video Search", or explicitly mentions the video field, the dataify-google-videos skill is triggered. It is an AI Agent Skill for Claude Code / OpenClaw, with 45 downloads so far.

How do I install Dataify Google Videos?

Run "/install dataify-google-videos" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Dataify Google Videos free?

Yes, Dataify Google Videos is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Dataify Google Videos support?

Dataify Google Videos is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Dataify Google Videos?

It is built and maintained by dataify-server (@dataify-server); the current version is v1.0.0.

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