AI Image Generation and Editing
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
Enhance images and videos using HitPaw's AI enhancement API. An agent skill from LeoYeAI/openclaw-master-skills.
Install Hitpaw Image Enhancer
$ npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills hitpaw-image-enhancer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hitpaw-image-enhancer .claude/skills/hitpaw-image-enhancer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "hitpaw-image-enhancer" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancer into .claude/skills/hitpaw-image-enhancer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hitpaw-image-enhancer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills hitpaw-image-enhancer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/hitpaw-image-enhancer .agents/skills/hitpaw-image-enhancer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "hitpaw-image-enhancer" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancer into .agents/skills/hitpaw-image-enhancer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hitpaw-image-enhancer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills hitpaw-image-enhancer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/hitpaw-image-enhancer .cursor/skills/hitpaw-image-enhancer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "hitpaw-image-enhancer" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancer into .cursor/skills/hitpaw-image-enhancer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hitpaw-image-enhancer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/hitpaw-image-enhancer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills hitpaw-image-enhancer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/hitpaw-image-enhancer .gemini/skills/hitpaw-image-enhancer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "hitpaw-image-enhancer" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancer into .gemini/skills/hitpaw-image-enhancer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hitpaw-image-enhancer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills hitpaw-image-enhancerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/hitpaw-image-enhancer .github/skills/hitpaw-image-enhancer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "hitpaw-image-enhancer" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancer into .github/skills/hitpaw-image-enhancer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hitpaw-image-enhancer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills hitpaw-image-enhancer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/hitpaw-image-enhancer .opencode/skills/hitpaw-image-enhancer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "hitpaw-image-enhancer" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/hitpaw-image-enhancer into .opencode/skills/hitpaw-image-enhancer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hitpaw-image-enhancer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
hitpaw-image-enhancer- GitHub stars
- 2.2k
- Token cost
- ~4.5k tokens
- SKILL.md length
- 1,581 words
- Files
- 11
- Skills in repo
- 1,235
- Repo updated
- First seen
- Licence
- MIT
At a glance
Enhance images and videos using HitPaw's AI enhancement API. An agent skill from LeoYeAI/openclaw-master-skills.
- Tasks that involve Image editing
- SKILL.md covers 🎯 Features, 📸 Image Enhancement, 🎬 Video Enhancement and 🚀 Why Choose HitPaw API?, plus 8 more sections
- Runs JavaScript and TypeScript scripts from its folder; reaches api-base.hitpaw.com; needs HITPAW_API_KEY
What it does
Hitpaw Image Enhancer is an agent skill from LeoYeAI/openclaw-master-skills. Enhance images and videos using HitPaw's AI enhancement API
Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files (for example `DEV.md`, `README.md` and `_meta.json`).
It sits in Media & Creative, covering Image editing. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
When your agent uses it
- Tasks that involve Image editing
Example prompts
- “/hitpaw-image-enhancer”
Requirements
- Node.js
- A credential in HITPAW_API_KEY
What it can do on your machine
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (JavaScript and TypeScript), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api-base.hitpaw.com
Also links to:
developer.hitpaw.complayground.hitpaw.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
HITPAW_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Hitpaw Image Enhancer loads about 4.5k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 1,581 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:234
Or create a `.env` file in your OpenClaw workspace:
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,581 words, ~4,527 tokens.
Download SKILL.mdSave it as
.claude/skills/hitpaw-image-enhancer/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.- name
- hitpaw-image-enhancer
- description
- Enhance images and videos using HitPaw's AI enhancement API
- version
- 1.0.1
- author
- Nova (HitPaw-Official)
- type
- cli
- entry
- dist/cli.js
- repository
- https://github.com/HitPaw-Official/openclaw-skill-hitpaw-enhancer
- keywords
- image, video, enhancement, upscale, hitpaw, ai
- license
- MIT
- capabilities
- image_enhancement, image_upscaling, photo_enhance, video_enhancement, video_upscaling
- requirements.node
- >=18
- requirements.packages
- axios, commander, ora, chalk, fs-extra
HitPaw Image & Video Enhancer Skill
A powerful OpenClaw skill that integrates HitPaw's state-of-the-art AI enhancement technology for both images and videos. Enhance, upscale, restore, and denoise with multiple AI models.
🎯 Features
Based on the official HitPaw API Documentation, this skill leverages industrial-grade AI models developed in-house by HitPaw's expert R&D team.
Core Strengths
- Quality: Industry-defining quality fit for professional use cases, from commercial photography to archival restoration
- Fidelity: Preserves the original details and identities in the source images, ensuring the output remains true to the input
- Efficiency: Optimized for low latency and high throughput, capable of processing distinct enhancement tasks at scale
📸 Image Enhancement
According to the Image API Introduction, our image processing services offer world-class capabilities designed to handle a wide variety of restoration scenarios:
Key Capabilities
- Upscale: Output high-resolution images from low-resolution input files using standard or high-fidelity models
- Face Recovery: Ensure high-quality facial details, offering both "Clear" (soft/beauty) and "Natural" (textured/realistic) restoration options
- Sharpen & Denoise: Bring images into focus by removing blur and sensor noise while preserving the original structure
- Generative Restoration: Leverage Diffusion technology to reconstruct details in severely degraded portraits or general images
Model Classes
The Image API offers two classes of AI models to suit different needs:
- Standard Models: Fast and efficient, prioritizing preserving original fidelity and details. Recommended for most professional and general restoration use cases
- Generative Models: Utilize Stable Diffusion to produce the highest quality outputs, capable of "imagining" missing details. Ideal for extremely low-quality inputs where traditional upscaling fails
Standard Models
As detailed in the Available Models documentation:
| Model | Multiplier | Description | Best For |
|---|---|---|---|
general_2x / general_4x | 2x / 4x | General Enhance Model | General photos, landscapes |
face_2x / face_4x | 2x / 4x | Portrait Model (Clear) | Soft/beauty style portrait enhancement |
face_v2_2x / face_v2_4x | 2x / 4x | Portrait Model (Natural) | Natural/realistic portrait enhancement |
high_fidelity_2x / high_fidelity_4x | 2x / 4x | High Fidelity Model | Professional photography, conservatively upscaling high-quality sources |
sharpen_denoise_1x | 1x | Sharp Denoise Model | Aggressive denoising with sharpening |
detail_denoise_1x | 1x | Detail Denoise Model | Gentle denoising with texture preservation |
Generative Models
Powered by Stable Diffusion technology:
| Model | Multiplier | Description | Best For |
|---|---|---|---|
generative_portrait_1x/2x/4x | 1x/2x/4x | Generative Portrait Model | Extremely low-quality portraits, "re-imagines" details |
generative_general_1x/2x/4x | 1x/2x/4x | Generative Enhance Model | Heavily compressed or very low-resolution general images |
Technical Highlights:
- Generative models excel at texture generation and sharpening
- They can fill in missing details that traditional upscalers cannot recover
- Ideal for restoration tasks where source data is severely degraded
Example Image Use Cases
# General photo upscaling (landscape, architecture)
enhance-image -u landscape.jpg -m general_4x -o hd_landscape.jpg
# Portrait beautification (soft skin)
enhance-image -u selfie.jpg -m face_4x -o portrait_beautified.jpg
# Professional archival restoration (natural look)
enhance-image -u old_photo.png -m face_v2_2x -o restored.png --keep-exif
# Denoise grainy low-light photo
enhance-image -u night_photo.jpg -m sharpen_denoise_1x -o clean.jpg
# Generative reconstruction for severely degraded image
enhance-image -u blurry_face.jpg -m generative_portrait_2x -o ai_face.jpg🎬 Video Enhancement
According to the Video API Introduction, our video processing services provide industrial-grade solutions for restoring and upscaling video content:
Key Capabilities
- Video Upscale: Convert SD or HD footage to 4K Ultra HD clarity using deep convolution and feature learning technologies
- Portrait Restoration: Specialized models to detect, stabilize, and enhance faces in video streams, removing motion blur and noise while maintaining identity
- General Restoration: A comprehensive solution based on GAN technology to de-noise, de-blur, and enhance details in general video content
- Generative Reconstruction: Utilizing Stable Diffusion for video to reconstruct textures and details in extremely low-quality footage
Core Pillars
- Temporal Stability: Unlike image-only models, our video engines ensure smooth transitions between frames, eliminating flickering and jitter
- Clarity: Recovering fine details and removing compression artifacts common in streaming or legacy media
- Performance: Optimized inference times to handle heavy video processing workloads efficiently
Model Classes
- Restoration & Upscale (Standard): Models like Ultra HD and General Restore focus on cleaning up the footage and increasing resolution without altering the fundamental content. They rely on pixel-perfect accuracy and temporal consistency
- Generative Video: Uses advanced logic-based reconstruction. Designed for "impossible" restoration tasks where the source video lacks sufficient data, generating realistic textures and details to fill the gaps
Available Video Models
From the Video Models Documentation:
| Model | Description | Use Case |
|---|---|---|
ultrahd_restore_2x | Ultra HD Model | High-definition upscale; natural-looking 1080p→4K |
general_restore_1x / 2x / 4x | General Restore Model | General video restoration, de-noising, de-blurring |
portrait_restore_1x / 2x | Portrait Restore Model | Multi-face restoration with temporal stability |
face_soft_2x | Video Face Soft Model | Facial beautification with consistent appearance |
generative_1x | Generative Video Model | Extreme restoration of heavily degraded footage |
Technical Highlights:
- Generates realistic textures and eliminates flickering via multi-frame SD architecture
- Handles heavy compression, high-ISO noise, and complex motion blur
- Maintains identity consistency across frames
Example Video Use Cases
# Convert old 720p footage to 4K
enhance-video -u old_clip.mp4 -m ultrahd_restore_2x -r 3840x2160 -o 4k_remastered.mp4
# Restore grainy, noisy home video
enhance-video -u home_movie.avi -m general_restore_2x -r 1920x1080 -o cleaned.mp4
# Beautify faces in vlog/interview
enhance-video -u interview.mp4 -m face_soft_2x -r 1920x1080 -o soft_faces.mp4
# Stabilize and restore old family footage with multiple faces
enhance-video -u family_reunion.mov -m portrait_restore_2x -r 1920x1080 -o restored.mp4
# Generative AI restoration for severely degraded source
enhance-video -u heavily_compressed.mp4 -m generative_1x -r 1920x1080 -o regenerated.mp4🚀 Why Choose HitPaw API?
Industry-Leading Quality: Professional-grade output suitable for commercial photography, archival restoration, and broadcast-quality video remastering
Unparalleled Fidelity: Strictly retains original details and subject identity, ensuring outputs remain true to inputs
Comprehensive Model Catalog: 16 specialized models covering virtually every restoration scenario
Scalable Performance: Optimized for low-latency, high-throughput workloads
📊 Quick Reference
Image Model Selection Guide
| Scenario | Recommended Model |
|---|---|
| General photo upscale | general_2x or general_4x |
| Portrait beautification | face_2x or face_4x |
| Portrait natural look | face_v2_2x or face_v2_4x |
| Professional archival | high_fidelity_2x / high_fidelity_4x |
| Grainy low-light | sharpen_denoise_1x |
| Subtle denoise | detail_denoise_1x |
| Severely degraded | generative_portrait_* or generative_general_* |
Video Model Selection Guide
| Scenario | Recommended Model |
|---|---|
| SD → 4K upscale | ultrahd_restore_2x |
| General cleanup | general_restore_2x |
| Interview/vlog beautification | face_soft_2x |
| Old home movies (multiple faces) | portrait_restore_2x |
| Severely compressed/ degraded | generative_1x |
Installation
clawhub install hitpaw-image-enhancerConfiguration
Set your HitPaw API key:
export HITPAW_API_KEY="your_api_key_here"Or create a .env file in your OpenClaw workspace:
HITPAW_API_KEY=your_api_key_hereGet your API key at: https://playground.hitpaw.com/
Test the API directly in the browser: HitPaw Playground →
📸 Examples & Gallery
Note: Place actual before/after screenshots in the
images/folder. Seeimages/README.mdfor guidelines.
Image Enhancement Examples
| Scenario | Before | After |
|---|---|---|
| General Upscale (2x) | Image: Before | Image: After |
| Face Enhancement | Image: Before | Image: After |
| Generative Portrait | Image: Before | Image: After |
Video Enhancement Examples
| Scenario | Original Frame | Enhanced Frame |
|---|---|---|
| General Restoration | Image: Original | Image: Enhanced |
| Portrait Restoration | Image: Before | Image: After |
IMAGE COMMAND
Usage: enhance-image
Command Line Options
| Option | Type | Default | Description |
|---|---|---|---|
--url, -u | string | required | URL of the image to enhance |
--output, -o | string | output.jpg | Output file path |
--model, -m | string | general_2x | Image model (see below) |
--extension, -e | string | .jpg | Output extension (.jpg, .png, .webp) |
--dpi | number | original | Target DPI for metadata |
--keep-exif | boolean | false | Preserve EXIF data from original |
--poll-interval | number | 5 | Polling interval in seconds |
--timeout | number | 300 | Maximum wait time in seconds |
Show full SKILL.md (617 more words)Show less
Available Image Models
| Model | Multiplier | Best For | DPI Support |
|---|---|---|---|
general_2x / general_4x | 2x / 4x | General photos, landscapes | ✅ |
face_2x / face_4x | 2x / 4x | Portrait & face enhancement | ✅ |
face_v2_2x / face_v2_4x | 2x / 4x | Improved face model | ✅ |
high_fidelity_2x / high_fidelity_4x | 2x / 4x | High quality preservation | ✅ |
sharpen_denoise_1x | 1x | Denoise & sharpen | ✅ |
detail_denoise_1x | 1x | Detail preservation | ✅ |
generative_* (1x/2x/4x) | — | AI generative fill | ❌ |
Examples
# Simple 2x upscale with general model
enhance-image -u photo.jpg -o enhanced.jpg -m general_2x
# Face enhancement 4x
enhance-image -u portrait.jpg -m face_4x -o portrait_4x.jpg --keep-exif
# High fidelity with custom DPI
enhance-image -u old-photo.png -m high_fidelity_2x -dpi 300 -o hd.png
# Batch processing
for img in *.jpg; do
enhance-image -u "$img" -o "upscaled/$img" -m general_4x
doneVIDEO COMMAND
Usage: enhance-video
⚠️ Important Notes
- Resolution is required (
--resolutionor-r). Must be inWIDTHxHEIGHTformat (e.g.,1920x1080). - Ensure target resolution does not exceed max output resolution (36 MP total pixels) per API limits.
- Video processing can take minutes to hours depending on length. Use
--timeoutto extend if needed. - Input video must be at a publicly accessible URL (local files not directly supported).
Command Line Options
| Option | Type | Default | Description |
|---|---|---|---|
--url, -u | string | required | URL of the video to enhance |
--output, -o | string | output.mp4 | Output file path |
--model, -m | string | general_restore_2x | Video model (see below) |
--resolution, -r | string | required | Target resolution in WxH (e.g., 1920x1080) |
--original-resolution | string | — | Original resolution (e.g., 1280x720) - optional |
--extension, -e | string | .mp4 | Output extension (.mp4, .mov, .avi) |
--fps | number | — | Target FPS (preserves original if omitted) |
--keep-audio | boolean | true | Preserve audio track |
--poll-interval | number | 10 | Polling interval in seconds |
--timeout | number | 600 | Maximum wait time in seconds |
Available Video Models
| Model | Description | Use Case |
|---|---|---|
general_restore_1x / 2x / 4x | General video restoration | General upscaling |
face_soft_2x | Face-softening enhancement | Portrait videos |
portrait_restore_1x / 2x | Portrait restoration | Face-focused content |
ultrahd_restore_2x | Ultra HD upscaling | Highest quality upscale |
generative_1x | Generative fill | AI-powered restoration |
Examples
# Upscale to 1080p using general_restore_2x
enhance-video -u input.mp4 -o output_1080p.mp4 -m general_restore_2x -r 1920x1080
# Upscale to 4K with specific original resolution
enhance-video -u clip.mov -o 4k.mov -m general_restore_4x -r 3840x2160 --original-resolution 1920x1080
# Denoise with portrait model
enhance-video -u portrait_video.avi -m portrait_restore_2x -r 1920x1080 -o clean_portrait.mp4
# Add color to B&W (if generative model supports)
enhance-video -u bw_vintage.mp4 -m generative_1x -r 1920x1080 -o colorized.mp4Coin Consumption
Image Enhancement
- 2x/4x models: ~75 coins per image
- 1x models: ~50 coins per image
- Generative models: ~100+ coins per image
Video Enhancement
Coin costs depend on video length, model, and resolution. Approximate rates:
- Upscale models: ~200-400 coins per minute
- Restoration models: ~150-300 coins per minute
Always check current rates at: https://playground.hitpaw.com/
Error Handling
Common errors and solutions:
| Error | Cause | Fix |
|---|---|---|
Invalid API key | Wrong or expired key | Update HITPAW_API_KEY |
Insufficient coins | Account balance too low | Top up at HitPaw Playground |
Unsupported model | Model name typo or not available | Check model table above |
Invalid extension | Output format not supported | Use .jpg/.png/.webp for images; .mp4/.mov/.avi for videos |
Invalid video URL | URL not publicly accessible | Ensure video is reachable via HTTPS |
Input/target resolution over limit | Exceeds 36 MP total pixels (e.g., 7680x4320 = ~33 MP) | Reduce resolution |
Video duration over limit | Video longer than 1 hour | Trim video first |
Rate limit exceeded | Too many requests | Wait and retry with exponential backoff |
Video processing failed | Corrupt video or unsupported codec | Try different input format or re-encode |
Technical Details
API Compatibility
This skill implements the official HitPaw API as documented:
- Base URL:
https://api-base.hitpaw.com - Image endpoint:
POST /api/photo-enhancer - Video endpoint:
POST /api/video-enhancer - Status endpoint:
POST /api/task-status
Both endpoints return a job_id. Use the status endpoint to poll until COMPLETED, then download from res_url.
Polling Strategy
- Images: default poll every 5s, timeout 300s (5 min)
- Videos: default poll every 10s, timeout 600s (10 min)
For longer videos, increase --timeout as needed (e.g., --timeout 3600 for 1 hour).
Resolution Handling
For videos, resolution is required. Choose based on your needs:
- Keep original size? Set
resolutionto original dimensions (use--original-resolutionfor better quality). - Upscale? Multiply original width/height by factor (2x, 4x).
- Downscale? Rare but possible; just specify smaller dimensions.
Max output: 36 megapixels total (width × height ≤ 36,000,000 pixels).
Examples: 3840×2160 = 8.3 MP ✅, 7680×4320 = 33.2 MP ✅, 8192×4608 = 37.7 MP ❌.
Audio Preservation
By default, enhance-video keeps the audio track (--keep-audio, default true). Use --no-keep-audio to strip audio.
Support
- Image API Docs: https://developer.hitpaw.com/image/API-reference
- Video API Docs: https://developer.hitpaw.com/video/API-reference
- Playground: https://playground.hitpaw.com/
- Contact: support@hitpaw.com
This skill is an unofficial integration with HitPaw API. You must have a valid API key and comply with HitPaw's terms. The skill author is not responsible for any charges incurred.
License
MIT © HitPaw-Official
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 10 other files in skills/hitpaw-image-enhancer of LeoYeAI/openclaw-master-skills.
- SKILL.md
- DEV.md
- README.md
- _meta.json
- images/README.md
- package-lock.json
- package.json
- src/cli.js
- src/client.ts
- src/video-cli.js
- tsconfig.json
Open the folder on GitHubat commit e5199b5
Compare with similar skills
Hitpaw Image Enhancer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Hitpaw Image Enhancer this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.5k | Automated safety check: Notes | MIT | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Generate Imageynulihao/AgentSkillOS | 618 | 10 repos | ~1.7k | Automated safety check: Notes | None | |
| GPT Image Generation CLIwuyoscar/GPT-Image2-Skill | 5.7k | — | ~2.5k | Automated safety check: Notes | MIT | |
| HyperFrames Media Useheygen-com/hyperframes | 60k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Media Useedenfunf/reelmimic | 1.9k | 1 repos | ~2k | Automated safety check: Pass | MIT |
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Generate or edit images using AI models (FLUX, Gemini). An agent skill from ynulihao/AgentSkillOS.
GPT Image Generation CLI
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Generates and edits images with GPT Image 2 or 2.5 through a packaged CLI and a prompt gallery, after settling which model fits the request.
HyperFrames Media Use
heygen-com/hyperframes
Finds, generates and edits media for HyperFrames video projects: music, sound effects, images, icons, logos, voiceovers, captions and color grades.
Media Use
edenfunf/reelmimic
Agent Media OS, the single skill for every media need in a HyperFrames project.
BlockRun Image Generation
BlockRunAI/ClawRouter
Generates or edits images through ClawRouter's local image API, with a choice of models and sizes and payment handled automatically through x402.
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Related
Categories
Questions about Hitpaw Image Enhancer
What does Hitpaw Image Enhancer do?
Enhance images and videos using HitPaw's AI enhancement API. An agent skill from LeoYeAI/openclaw-master-skills. Hitpaw Image Enhancer is an agent skill from LeoYeAI/openclaw-master-skills.
When should I use Hitpaw Image Enhancer?
Hitpaw Image Enhancer fits situations like: tasks that involve Image editing.
How do I install Hitpaw Image Enhancer in Claude Code?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a claude-code`. Or copy the skill folder (skills/hitpaw-image-enhancer in LeoYeAI/openclaw-master-skills) into .claude/skills/hitpaw-image-enhancer in your project. Claude Code loads it when a task matches its description.
How do I install Hitpaw Image Enhancer in Codex?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a codex`. Or copy the skill folder (skills/hitpaw-image-enhancer in LeoYeAI/openclaw-master-skills) into .agents/skills/hitpaw-image-enhancer in your project. Codex loads it when a task matches its description.
Can I use Hitpaw Image Enhancer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill hitpaw-image-enhancer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hitpaw-image-enhancer, .gemini/skills/hitpaw-image-enhancer, .github/skills/hitpaw-image-enhancer and .opencode/skills/hitpaw-image-enhancer in your project.
What does Hitpaw Image Enhancer need to run?
Going by SKILL.md and its folder, Hitpaw Image Enhancer needs JavaScript and TypeScript for the scripts in its folder and credentials named HITPAW_API_KEY. Our summary lists: Node.js; A credential in HITPAW_API_KEY.
Does Hitpaw Image Enhancer access the network?
SKILL.md names 3 domains. In commands or code: api-base.hitpaw.com; the agent is likely to contact it when it follows the instructions. As links in the text: developer.hitpaw.com and playground.hitpaw.com. This is read from the text; nothing was executed.
Is Hitpaw Image Enhancer safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Hitpaw Image Enhancer use?
Hitpaw Image Enhancer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Hitpaw Image Enhancer use?
About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Hitpaw Image Enhancer?
Skills that share tags, products or a category with Hitpaw Image Enhancer: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Generate Image (ynulihao/AgentSkillOS, 618 stars), GPT Image Generation CLI (wuyoscar/GPT-Image2-Skill, 5.7k stars) and HyperFrames Media Use (heygen-com/hyperframes, 60k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Hitpaw Image Enhancer?
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.