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dataify-server

Dataify Google Jobs

by dataify-server · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install dataify-google-jobs
Description
When the user requests "Call Google Jobs" or "Search for job/recruitment information and return the original response", or specifies the job search fields, t...
README (SKILL.md)

Dataify Google Jobs

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

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 Dataify Google Jobs fields. Use q as the job search query and set engine to the fixed value google_jobs.
  2. Build request parameters from the user-provided values plus documented defaults only. Defaults must come from the parameter descriptions in references/google_jobs_api.md; never treat examples as defaults.
    • engine: fixed google_jobs
    • json: default 1
    • google_domain: default google.com
    • no_cache: default false
    • All other parameters have no documented default and must stay unset unless the user provides them.
  3. Before every API call, show a Markdown table containing the complete body parameter list, excluding Authorization. The table must have exactly these columns: parameter name, current value, default value, description. Ask the user whether to modify the parameters. If the user requests changes, update the values and show the table again. Only call the API after the user confirms the table.
  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_jobs.py.
python3 scripts/google_jobs.py --q "software engineer jobs" --location "San Francisco" --gl us --hl en

Generate the confirmation table with:

python3 scripts/google_jobs.py --request "搜索 java 相关工作" --preview-table

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

python3 scripts/google_jobs.py --params-json '{"q":"software engineer jobs","location":"San Francisco","gl":"us","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_jobs.py --token "USER_TOKEN" --q "software engineer jobs" --location "San Francisco"

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

python3 scripts/google_jobs.py --request "搜索美国旧金山的软件工程师工作,语言英文,不使用缓存"
  1. Return the script output directly to the user. Do not summarize, extract, clean, translate, or reshape the API response body.

Field Mapping

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

Core rules:

  • Always submit the API request as form data with Content-Type: application/x-www-form-urlencoded.
  • Always force engine to google_jobs.
  • Keep request values as strings unless the script accepts and normalizes a boolean.
  • Ask a follow-up only when the required job 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.
  • Do not include Authorization in the preview table.
  • Do not call the API until the user confirms the preview table.

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
  • geographic search origin -> location
  • encoded Google location -> uule
  • next page -> next_page_token
  • chips/filter token from Google Jobs -> chips
  • search radius in kilometers -> lrad
  • work from home / remote-only filter -> ltype: "1" when requested
  • Google-provided filter string -> uds
  • bypass cache -> no_cache: "true"
Usage Guidance
Review before installing. Use DATAIFY_API_TOKEN from your environment instead of passing tokens on the command line, confirm that you understand every parameter before approving a call, and avoid putting sensitive job-search or location details into queries unless you are comfortable sending them to Dataify.
Capability Assessment
Purpose & Capability
The artifacts match the stated purpose: parse Google Jobs search parameters, require confirmation, and POST form data to Dataify's scraper API with engine fixed to google_jobs.
Instruction Scope
The trigger text is broad and the required confirmation table is forced into Chinese column labels/descriptions, which can weaken clear user consent for non-Chinese users before an external API call.
Install Mechanism
The package contains markdown references and two Python scripts with no install hooks, package dependencies, background services, or hidden setup behavior.
Credentials
Network access to https://scraperapi.dataify.com/request and use of DATAIFY_API_TOKEN are purpose-aligned for a Dataify API helper, and the skill repeatedly instructs the agent to confirm parameters before calling.
Persistence & Privilege
No persistent files, services, or privilege escalation were found, but the documented --token flow puts a credential in process arguments; using the environment variable is safer.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install dataify-google-jobs
  3. After installation, invoke the skill by name or use /dataify-google-jobs
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the dataify-google-jobs skill. - Triggers on user job search requests mentioning Google Jobs or relevant fields. - Guides users through a confirmation process, previewing all request parameters in a Markdown table before each API call. - Clearly distinguishes between required fields, documented defaults, and user-provided parameters—applies only documented defaults. - Requires explicit user confirmation for request parameters before making API calls. - Enforces token authentication, instructing users how to obtain a Dataify API token if missing. - Returns unmodified API responses directly to the user.
Metadata
Slug dataify-google-jobs
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Dataify Google Jobs?

When the user requests "Call Google Jobs" or "Search for job/recruitment information and return the original response", or specifies the job search fields, t... It is an AI Agent Skill for Claude Code / OpenClaw, with 36 downloads so far.

How do I install Dataify Google Jobs?

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

Is Dataify Google Jobs free?

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

Which platforms does Dataify Google Jobs support?

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

Who created Dataify Google Jobs?

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

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