An MCP server that provides on-demand skill loading for AI coding assistants.
Installable skillMITBy modbenderUpdated Oct 28, 2026
INTENDED FOROpenClawInstall in a listed agent.
instructions.md
---
name: hinge-liker-926c199f6191
description: "Automated Hinge dating profile liker using Android emulator + Gemini vision AI. Scrolls through full profiles, analyzes attractiveness with AI, likes the best photo/prompt with witty comments, skips others. Sends a detailed text report after each session. Use when asked to run Hinge likes, set up Hinge automation, check Hinge status, or manage daily dating app swiping."
---
# Hinge Auto-Liker
Automates Hinge swiping on an Android emulator. Uses Gemini vision to evaluate profiles, pick the best photo/prompt, and send witty comments.
## Requirements
- Android emulator (AVD) with Hinge installed and logged in
- `adb` in PATH
- `GEMINI_API_KEY` environment variable (Gemini 2.5 Flash recommended)
- Python 3.8+
- Java (for Android emulator)
## Setup (First Time)
1. Install Android command line tools (via Homebrew: `brew install --cask android-commandlinetools`)
2. Create an AVD: `avdmanager create avd -n HingePhone -k "system-images;android-34;google_apis;arm64-v8a" -d pixel_6`
3. Boot the emulator with a window, install Hinge from Play Store, and log in manually
4. Set `GEMINI_API_KEY` in environment
## Running
```bash
# Set environment
export PATH="<android-tools-path>/platform-tools:<android-tools-path>/emulator:$PATH"
export GEMINI_API_KEY="your-key-here"
# Boot emulator (windowed for video, add -no-window for headless)
emulator -avd HingePhone -no-audio -no-metrics -gpu swiftshader_indirect &
# Wait for boot
adb wait-for-device
while [ "$(adb shell getprop sys.boot_completed 2>/dev/null | tr -d '\r')" != "1" ]; do sleep 2; done
# Launch Hinge
adb shell am start -a android.intent.action.MAIN -n co.hinge.app/.ui.AppActivity
sleep 10
# Optional: start screen recording
adb shell screenrecord --time-limit 300 /sdcard/hinge_session.mp4 &
# Run the liker
python3 scripts/hinge_android.py --likes 8 --user-desc "a 25yo tech guy in SF who's fit and active"
# Pull recording + kill emulator
adb shell pkill -INT screenrecord; sleep 3
adb pull /sdcard/hinge_session.mp4 ./recordings/session.mp4
adb emu kill
```
## Script Options
| Flag | Default | Description |
|------|---------|-------------|
| `--likes` | 8 | Max likes per session |
| `--adb` | `adb` | Path to adb binary |
| `--user-desc` | generic | Description of the user for AI matching |
## Environment Variables
| Variable | Required | Description |
|----------|----------|-------------|
| `GEMINI_API_KEY` | Yes | Google Gemini API key |
| `GEMINI_MODEL` | No | Model name (default: `gemini-2.5-flash`) |
| `ADB_PATH` | No | Full path to adb binary |
| `HINGE_WORK_DIR` | No | Working directory for screenshots/logs |
## Output
The script prints a **session report** to stdout with:
- Total profiles seen, liked, skipped
- For each profile: who they are, why it liked/skipped, the comment sent, which content was liked
JSON logs are saved to `logs/` directory.
## Scheduling as a Daily Cron
Set up via OpenClaw cron for daily automated runs. Key notes:
- **Hardcode GEMINI_API_KEY in the cron payload** — cron shells don't source ~/.zshrc
- Use `am start` to launch Hinge, not `monkey` (more reliable)
- Compress videos before sending via iMessage (16MB limit): `ffmpeg -i input.mp4 -vcodec libx264 -crf 28 -preset fast -vf scale=720:-2 output.mp4`
## After Each Session
Send the user a text report including:
1. How many profiles seen / liked / skipped
2. For each liked profile: who she is, why the AI liked her, what comment was sent
3. For each skipped profile: brief reason why
4. Any errors (paywall, API failures, etc.)
5. Video recording if available (compressed for messaging)
## Troubleshooting
- **Paywall/out of likes**: Free likes reset ~24h after last batch. Schedule runs accordingly.
- **Gemini empty responses**: Increase `maxOutputTokens`, check API key/quota.
- **Can't find buttons**: Hinge UI changes periodically — check `find_all_hearts()` and `find_skip_button()` patterns.
- **Emulator crashes**: Check disk space (`df -h`), try `-gpu swiftshader_indirect`.
---
name: hinge-liker-926c199f6191
description: "Automated Hinge dating profile liker using Android emulator + Gemini vision AI. Scrolls through full profiles, analyzes attractiveness with AI, likes the best photo/prompt with witty comments, skips others. Sends a detailed text report after each session. Use when asked to run Hinge likes, set up Hinge automation, check Hinge status, or manage daily dating app swiping."
---
# Hinge Auto-Liker
Automates Hinge swiping on an Android emulator. Uses Gemini vision to evaluate profiles, pick the best photo/prompt, and send witty comments.
## Requirements
- Android emulator (AVD) with Hinge installed and logged in
- `adb` in PATH
- `GEMINI_API_KEY` environment variable (Gemini 2.5 Flash recommended)
- Python 3.8+
- Java (for Android emulator)
## Setup (First Time)
1. Install Android command line tools (via Homebrew: `brew install --cask android-commandlinetools`)
2. Create an AVD: `avdmanager create avd -n HingePhone -k "system-images;android-34;google_apis;arm64-v8a" -d pixel_6`
3. Boot the emulator with a window, install Hinge from Play Store, and log in manually
4. Set `GEMINI_API_KEY` in environment
## Running
```bash
# Set environment
export PATH="<android-tools-path>/platform-tools:<android-tools-path>/emulator:$PATH"
export GEMINI_API_KEY="your-key-here"
# Boot emulator (windowed for video, add -no-window for headless)
emulator -avd HingePhone -no-audio -no-metrics -gpu swiftshader_indirect &
# Wait for boot
adb wait-for-device
while [ "$(adb shell getprop sys.boot_completed 2>/dev/null | tr -d '\r')" != "1" ]; do sleep 2; done
# Launch Hinge
adb shell am start -a android.intent.action.MAIN -n co.hinge.app/.ui.AppActivity
sleep 10
# Optional: start screen recording
adb shell screenrecord --time-limit 300 /sdcard/hinge_session.mp4 &
# Run the liker
python3 scripts/hinge_android.py --likes 8 --user-desc "a 25yo tech guy in SF who's fit and active"
# Pull recording + kill emulator
adb shell pkill -INT screenrecord; sleep 3
adb pull /sdcard/hinge_session.mp4 ./recordings/session.mp4
adb emu kill
```
## Script Options
| Flag | Default | Description |
|------|---------|-------------|
| `--likes` | 8 | Max likes per session |
| `--adb` | `adb` | Path to adb binary |
| `--user-desc` | generic | Description of the user for AI matching |
## Environment Variables
| Variable | Required | Description |
|----------|----------|-------------|
| `GEMINI_API_KEY` | Yes | Google Gemini API key |
| `GEMINI_MODEL` | No | Model name (default: `gemini-2.5-flash`) |
| `ADB_PATH` | No | Full path to adb binary |
| `HINGE_WORK_DIR` | No | Working directory for screenshots/logs |
## Output
The script prints a **session report** to stdout with:
- Total profiles seen, liked, skipped
- For each profile: who they are, why it liked/skipped, the comment sent, which content was liked
JSON logs are saved to `logs/` directory.
## Scheduling as a Daily Cron
Set up via OpenClaw cron for daily automated runs. Key notes:
- **Hardcode GEMINI_API_KEY in the cron payload** — cron shells don't source ~/.zshrc
- Use `am start` to launch Hinge, not `monkey` (more reliable)
- Compress videos before sending via iMessage (16MB limit): `ffmpeg -i input.mp4 -vcodec libx264 -crf 28 -preset fast -vf scale=720:-2 output.mp4`
## After Each Session
Send the user a text report including:
1. How many profiles seen / liked / skipped
2. For each liked profile: who she is, why the AI liked her, what comment was sent
3. For each skipped profile: brief reason why
4. Any errors (paywall, API failures, etc.)
5. Video recording if available (compressed for messaging)
## Troubleshooting
- **Paywall/out of likes**: Free likes reset ~24h after last batch. Schedule runs accordingly.
- **Gemini empty responses**: Increase `maxOutputTokens`, check API key/quota.
- **Can't find buttons**: Hinge UI changes periodically — check `find_all_hearts()` and `find_skip_button()` patterns.
- **Emulator crashes**: Check disk space (`df -h`), try `-gpu swiftshader_indirect`.
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.
When the user wants to understand, reduce, or recover from developer churn. Trigger phrases include "why developers leave," "churn rate," "win-back campaign," "at-risk users," "developer retention," "preventing churn," or "competitor switching."
ClaudeCodexCursorSales
jonathimer/devmarketing-skills contributors, via Agentic Awesome Skills
Uncover the functional, emotional and social jobs a customer hires a product to do: progress state, hiring trigger, alternatives, success criteria, JTBD map. Use when you need to understand why users buy, switch or churn, or to anchor positioning, messaging and onboarding in real jobs.
Hilft bei Anlagenliste Verstehen für Menschen mit Deutsch als Zweitsprache. Erklaert Juristendeutsch, klaert Risiko, Frist und naechste Handlung, und formuliert respektvoll in einfachem oder formalem Deutsch im Juristische Sprache Deutsch Als Zweitsprache.