Dataify Google Images
Use this skill to turn a user's Google Images request into a Dataify Scraper API form submission.
Workflow
- Parse the user's request into Google Images fields. Use
qas the image search query and setenginetogoogle_images. - Apply documented defaults when the user does not specify a value. Use only defaults stated in the parameter descriptions:
json=1,google_domain=google.com,start=0,nfpr=0,filter=1,device=desktop, andno_cache=false. Do not treat examples such aspizza,us,en,radius=10,tbm=isch,render_js=true, orai_overview=trueas defaults. - If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain
DATAIFY_API_TOKEN. - Build request parameters with the fields the user requested plus documented defaults. The script submits these parameters as form data, not a JSON request body.
- Run the bundled Python script with
python3. Run it from this skill directory, or use the absolute path toscripts/google_images.py.
python3 scripts/google_images.py --q "red sneakers" --json 1
For many fields, pass one JSON object with shell-appropriate quoting. The script will still submit form data to the API:
python3 scripts/google_images.py --params-json '{"q":"red sneakers","json":"1","google_domain":"google.com","gl":"us","hl":"en","device":"mobile"}'
Field Mapping
Use references/google_images_api.md when you need the exact field list, defaults, constraints, or examples.
Core rules:
- Always submit the API request as form data with
Content-Type: application/x-www-form-urlencoded. - Always force
enginetogoogle_images. - Keep request values as strings unless the script accepts and normalizes a boolean.
- Include documented default values when the user did not request a value. Omit optional fields only when they have no documented default and the user did not request them.
- Ask a follow-up only when the required image query
qcannot be inferred. - If
uuleis present, omitlocation,lat,lon, andradius. - If
locationis present, omituule,lat, andlon. - Use
latandlontogether. If only one is available, ask for the missing coordinate. - Normalize token values in the script. A token without
Beareris 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 - country-restricted results ->
cr, formatted likecountryFR - language-restricted results ->
lr, formatted likelang_fr - named search origin ->
location - Google encoded location ->
uule - GPS coordinates ->
latandlon - location bias radius in meters ->
radius - page number N ->
start: String((N - 1) * 10) - advanced image filters, size, color, type, rights, or date ->
tbs - safe search on/off ->
safe: "active"orsafe: "off" - desktop/tablet/mobile ->
device - render JavaScript ->
render_js: "true" - bypass cache ->
no_cache: "true" - include AI Overview ->
ai_overview: "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_images.py --q "red sneakers" --json 1
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 (
exportfor macOS/Linux shells,$env:for Windows PowerShell, orsetfor 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_TOKENis 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
.envunless the execution path explicitly loads it, and ensure.envis 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.
