Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Automates Hinge swiping on an Android emulator. Uses Gemini vision AI to evaluate profiles, select the best photo or prompt, and send a generated witty comment. After each session, outputs a detailed report of profiles seen, liked, skipped, and comments sent.
Combines Android emulator automation with vision AI to make context-aware like decisions rather than random or threshold-based swiping.
When to use it
- Running daily Hinge likes without manual swiping
- Letting AI pick the best photo to like on a profile
- Getting a session summary of who was liked and why
- Scheduling automated swipe sessions via cron
- Reviewing skipped profiles with AI-generated reasoning
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: run 8 Hinge likes for me
- 1Boots the Android emulator with the HingePhone AVD
- 2Launches the Hinge app via adb shell am start
- 3Runs hinge_android.py with --likes 8 and user description
- 4Gemini vision evaluates each profile and selects the best photo or prompt to like
- 5Sends witty AI-generated comment and logs result for each profile
Session report: 12 profiles seen, 8 liked, 4 skipped — includes who each liked person is, the comment sent, and skip reasons for the rest
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.