Dataify Google Lens#

Use this skill to turn a user's Google Lens or reverse-image-search request into a Dataify Scraper API form submission.

Workflow#

1. Parse the user's request into Google Lens fields. Use url for the image URL, set engine to google_lens, and infer optional fields only when the user asks for them.
2. Build request parameters from the user's request. If the user did not specify a field, use only the documented default from the parameter description:
   • engine: google_lens
   • json: 1
   • type: all
   • no_cache: false Fields with no documented default stay unset. Do not treat examples such as us, en, active, or true as defaults.

bash

python3 scripts/google_lens.py --url "https://example.com/image.jpg" --json 1 --type all --country us --preview

Ask the user: 请确认是否需要修改这些参数；确认无误后我再调用接口。

1. If the token is missing, stop and tell the user to sign in at Dataify Dashboard to obtain DATAIFY_API_TOKEN.
2. Run the bundled Python script with python3. Run it from this skill directory, or use the absolute path to scripts/google_lens.py. The script submits form data to the hardcoded API endpoint; it does not send a JSON body.

bash

python3 scripts/google_lens.py --url "https://example.com/image.jpg" --json 1 --type all --country us

Natural-language fallback is available when useful:

bash

python3 scripts/google_lens.py --request "Search Google Lens for https://example.com/image.jpg, products, country US, safe on, no cache"

Field Mapping#

Use references/google_lens_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 encode request data as UTF-8.
• Always force engine to google_lens.
• Keep request values as strings unless the script accepts and normalizes a boolean.
• Use documented defaults when the user does not specify a value. Omit fields that have no documented default and were not requested.
• Ask a follow-up only when the required image url cannot be inferred from the user's request.
• Normalize token values in the script. A token without Bearer is accepted and prefixed automatically.
• Never include Authorization in the preview table, and never print the token value in the final explanation.

Common mappings:

• Image URL, picture URL, reverse image search target -> url
• "JSON" -> json: "1"
• "JSON+HTML" -> json: "2"
• "HTML" -> json: "3"
• "Light JSON" -> json: "4"
• interface/search language -> hl
• country or region for Lens behavior -> country
• all results -> type: "all"
• product results -> type: "products"
• about this image -> type: "about_this_image"
• exact matches -> type: "exact_matches"
• visual matches or similar images -> type: "visual_matches"
• extra query/keyword/refinement used with all, visual_matches, or products -> q
• safe search on/off -> safe: "active" or safe: "off"
• 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_lens.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.