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Agent Skill · 图像处理

hitpaw-image-enhancer(hitpaw 图像增强器)

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

hitpaw-image-enhancer 是图像处理类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在图像处理类的 1,562 个 Skill 里排第 255。

总安装 13,003周安装 526GitHub Stars 1下载 4,082核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.4

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hitpaw-image-enhancer(hitpaw 图像增强器)
来源仓库:https://github.com/hitpawdev/hitpaw-image-enhancer
安装命令:
openclaw skills install hitpaw-image-enhancer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install hitpaw-image-enhancer

这个 Skill 是做什么的

图像处理类 Skill 处理生成、裁剪、压缩和批量转换图片的任务。

用于辅助图像生成与编辑,支持文本到图片转换及画质增强处理。适用于视觉素材制作、背景优化等图像处理需求。通过 openclaw skills install 命令从 clawhub 安装使用。需确认输入图片版权、输出格式限制及模型适用范围。

hitpaw-image-enhancer 属于图像处理类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install hitpaw-image-enhancer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

hitpaw-image-enhancer 怎么安装?

在终端执行 openclaw skills install hitpaw-image-enhancer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

hitpaw-image-enhancer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

hitpaw-image-enhancer 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

hitpaw-image-enhancer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

hitpaw-image-enhancer 用的人多吗?

公开数据是累计安装 13,003 次,近一周安装 526 次,下载 4,082 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

hitpaw-image-enhancer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理图像处理类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

图像处理类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
ai-image-generation

AI 图像生成 · Codex、Claude

4,365,552382调用外部服务未明确有提醒
openai-image-gen

OpenAI 图像生成 · OpenClaw

1,906,88432需要联网MIT-0有提醒
image

图像 · OpenClaw

525,99926需要联网MIT-0通过
baoyu-cover-image

宝玉封面图 · Codex、Claude

474,24016,779只读MIT有提醒
baoyu-image-gen

宝玉图像生成器 · Codex、Claude

468,00716,778接触敏感数据MIT通过
hitpaw-image-enhancer

hitpaw 图像增强器 · 本页

13,0031接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
hitpaw-image-enhancer
description
Enhance images and videos using HitPaw's AI enhancement API
version
1.0.3
author
Nova (HitPaw-Official)
type
cli
entry
dist/cli.js
repository
https://github.com/HitPaw-Official/openclaw-skill-hitpaw-enhancer
keywords
license
MIT
capabilities
requirements
node
>=18
packages
environment
variables
description
Your HitPaw API key
required
true

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:

ModelMultiplierDescriptionBest For
general_2x / general_4x2x / 4xGeneral Enhance ModelGeneral photos, landscapes
face_2x / face_4x2x / 4xPortrait Model (Clear)Soft/beauty style portrait enhancement
face_v2_2x / face_v2_4x2x / 4xPortrait Model (Natural)Natural/realistic portrait enhancement
high_fidelity_2x / high_fidelity_4x2x / 4xHigh Fidelity ModelProfessional photography, conservatively upscaling high-quality sources
sharpen_denoise_1x1xSharp Denoise ModelAggressive denoising with sharpening
detail_denoise_1x1xDetail Denoise ModelGentle denoising with texture preservation
Generative Models

Powered by Stable Diffusion technology:

ModelMultiplierDescriptionBest For
generative_portrait_1x/2x/4x1x/2x/4xGenerative Portrait ModelExtremely low-quality portraits, "re-imagines" details
generative_1x/2x/4x1x/2x/4xGenerative Enhance ModelHeavily 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:

ModelDescriptionUse Case
ultrahd_restore_2xUltra HD ModelHigh-definition upscale; natural-looking 1080p→4K
general_restore_1x / 2x / 4xGeneral Restore ModelGeneral video restoration, de-noising, de-blurring
portrait_restore_1x / 2xPortrait Restore ModelMulti-face restoration with temporal stability
face_soft_2xVideo Face Soft ModelFacial beautification with consistent appearance
generative_1xGenerative Video ModelExtreme 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

ScenarioRecommended Model
General photo upscalegeneral_2x or general_4x
Portrait beautificationface_2x or face_4x
Portrait natural lookface_v2_2x or face_v2_4x
Professional archivalhigh_fidelity_2x / high_fidelity_4x
Grainy low-lightsharpen_denoise_1x
Subtle denoisedetail_denoise_1x
Severely degradedgenerative_portrait_* or generative_*

Video Model Selection Guide

ScenarioRecommended Model
SD → 4K upscaleultrahd_restore_2x
General cleanupgeneral_restore_2x
Interview/vlog beautificationface_soft_2x
Old home movies (multiple faces)portrait_restore_2x
Severely compressed/ degradedgenerative_1x

Installation

clawhub install hitpaw-image-enhancer

Configuration

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_here

Get your API key at: https://playground.hitpaw.com/

Test the API directly in the browser: HitPaw Playground →


📸 Examples & Gallery

Note: All screenshots below are from official HitPaw website (hitpaw.com), showcasing real enhancement results. Place additional examples in the images/ folder.

Image Enhancement Examples

General Upscale (2x/4x)

From official HitPaw documentation:

BeforeAfter
BeforeAfter

*Demonstrates general image enhancement and upscaling capabilities*

Use case: Landscape photos, architecture, general photography

Unblur / Motion Blur Removal
BeforeAfter
BlurrySharp

*Shows blur removal and sharpening effects*

Use case: Action shots, low-light photos, camera shake recovery


🎬 Video Enhancement Gallery

Video screenshots coming soon. Currently using placeholder references.
ScenarioOriginal FrameEnhanced Frame
General Upscale (1080p → 4K)OriginalEnhanced
Portrait RestorationBeforeAfter
Denoise & CleanupNoisyClean

See images/README.md for screenshot guidelines and recommended sources.


📊 Model Comparison Examples

Face Enhancement: Clear vs Natural

Clear (Soft/Beauty)Natural (Realistic)
Face ClearFace Natural
  • Face Clear Model: Soft skin, beautification style
  • Face Natural Model: Preserves natural texture and pores

Generative vs Standard Models

Standard (general_4x)Generative (generative_portrait_2x)
StandardGenerative
  • Standard models: Fast, preserves original details
  • Generative models: Reconstructs missing details, ideal for severely degraded inputs

IMAGE COMMAND

Usage: enhance-image

Command Line Options

OptionTypeDefaultDescription
--url, -ustringrequiredURL of the image to enhance
--output, -ostringoutput.jpgOutput file path
--model, -mstringgeneral_2xImage model (see below)
--extension, -estring.jpgOutput extension (.jpg, .png, .webp)
--dpinumberoriginalTarget DPI for metadata
--keep-exifbooleanfalsePreserve EXIF data from original
--poll-intervalnumber5Polling interval in seconds
--timeoutnumber300Maximum wait time in seconds
Available Image Models
ModelMultiplierBest ForDPI Support
general_2x / general_4x2x / 4xGeneral photos, landscapes✅
face_2x / face_4x2x / 4xPortrait & face enhancement✅
face_v2_2x / face_v2_4x2x / 4xImproved face model✅
high_fidelity_2x / high_fidelity_4x2x / 4xHigh quality preservation✅
sharpen_denoise_1x1xDenoise & sharpen✅
detail_denoise_1x1xDetail preservation✅
generative_1x/2x/4x—Generative Enhance Model❌
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
done

VIDEO COMMAND

Usage: enhance-video

⚠️ Important Notes

  • Resolution is required (--resolution or -r). Must be in WIDTHxHEIGHT format (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 --timeout to extend if needed.
  • Input video must be at a publicly accessible URL (local files not directly supported).

Command Line Options

OptionTypeDefaultDescription
--url, -ustringrequiredURL of the video to enhance
--output, -ostringoutput.mp4Output file path
--model, -mstringgeneral_restore_2xVideo model (see below)
--resolution, -rstringrequiredTarget resolution in WxH (e.g., 1920x1080)
--original-resolutionstring—Original resolution (e.g., 1280x720) - optional
--extension, -estring.mp4Output extension (.mp4, .mov, .avi)
--fpsnumber—Target FPS (preserves original if omitted)
--keep-audiobooleantruePreserve audio track
--poll-intervalnumber10Polling interval in seconds
--timeoutnumber600Maximum wait time in seconds
Available Video Models
ModelDescriptionUse Case
general_restore_1x / 2x / 4xGeneral video restorationGeneral upscaling
face_soft_2xFace-softening enhancementPortrait videos
portrait_restore_1x / 2xPortrait restorationFace-focused content
ultrahd_restore_2xUltra HD upscalingHighest quality upscale
generative_1xGenerative fillAI-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.mp4

Coin 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:

ErrorCauseFix
Invalid API keyWrong or expired keyUpdate HITPAW_API_KEY
Insufficient coinsAccount balance too lowTop up at HitPaw Playground
Unsupported modelModel name typo or not availableCheck model table above
Invalid extensionOutput format not supportedUse .jpg/.png/.webp for images; .mp4/.mov/.avi for videos
Invalid video URLURL not publicly accessibleEnsure video is reachable via HTTPS
Input/target resolution over limitExceeds 36 MP total pixels (e.g., 7680x4320 = ~33 MP)Reduce resolution
Video duration over limitVideo longer than 1 hourTrim video first
Rate limit exceededToo many requestsWait and retry with exponential backoff
Video processing failedCorrupt video or unsupported codecTry different input format or re-encode

Error Codes

The API returns structured error codes. Always check both HTTP status and the error_code field.

General Errors

error_codeHTTP StatusMessage
100400000400No access
100400001400Invalid URL
100400002400Bad Request
100401000401Token is expired
100403000403Invalid request parameters
100403001403Access denied
100403002403You don't have permission to access this resource
100429000429Too many requests, please try again later
100500000500Internal error
100500001500Database error
100500002500Cache error
100500003500Failed to create file
100500004500Signature verification failed
100500005500Configuration error
100500006500Unknown error
100500007500Operation timeout

API-Specific Errors

error_codeHTTP StatusMessage
110400000400api_key is not valid
110400002400The task does not exist
110400003400The task failed, please try again
110400005400The model is not supported, please try again
110400007400The extension is not valid
110400008400The video URL is not valid
110400009400The input resolution is over limit
110400010400The target resolution is over limit
110400011400The video duration is over limit
110402000402The coins are not enough
110402001402The coins are not enough
110402004402The Demo try times exceeded

Error Response Format

{
  "error_code": 110400000,
  "message": "api_key is not valid"
}

Rate Limiting

  • The API implements rate limiting to ensure fair usage
  • Error code 100429000 will be returned if you exceed the rate limit
  • Implement exponential backoff in your retry logic

Best Practices

Polling for Job Status

  • Poll the /api/task-status endpoint at reasonable intervals (recommended: every 5–10 seconds)
  • Implement exponential backoff for failed requests
  • Set a maximum number of polling attempts to avoid infinite loops
  • Check status values: CONVERTING (keep polling), COMPLETED (success), ERROR (failed)

Error Handling

  • Always check the HTTP status code AND error_code in the response
  • Implement retry logic for transient errors (5xx errors)
  • Do NOT retry 4xx client errors without first fixing the request
  • Log error responses for debugging

Resource Limits

  • Images: Max input resolution 70 MP (Enhancement/Denoise) / 34 MP (Generative); Max output 432 MP (Enhancement/Denoise)
  • Videos: Max output 36 MP total pixels; Duration 0.5s – 1 hour
  • Verify file extension validity before submitting

API Key Management

  • Store API keys securely using environment variables
  • Never commit API keys to version control
  • Rotate API keys periodically

File URL Requirements

  • Ensure image and video URLs are publicly accessible
  • Use HTTPS URLs
  • Use Pre-sign OSS Upload for unreliable URLs: https://developer.hitpaw.com/common/oss-presign-put-api

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)
  • Implement exponential backoff when encountering 5xx errors or rate limit (429)

For longer videos, increase --timeout as needed (e.g., --timeout 3600 for 1 hour).

Resolution & Format Limits

Image Model Specs:

Model CategoryDPI SupportMax InputMax OutputFormats
Enhancement & Denoise (general_*, face_*, high_fidelity_*, *_denoise_*)✅70 MP432 MPbmp, jpeg, jpg, png, jfif, tga, tiff, webp, heif
Generative (generative_*, generative_portrait_*)❌34 MP34 MPSame formats

Video Model Specs:

PropertyLimit
Max Input ResolutionNo limit
Max Output36 MP total pixels
Duration0.5 seconds – 1 hour
Input Formatsdv, mlv, m2ts, m2t, m2v, nut, ser, 3g2, 3gp, asf, avi, divx, f4v, flv, h261, h263, m4v, mkv, mov, mp4, mpeg, mpeg4, mpg, mxf, ogv, rm, rmvb, webm, wmv, gif
Output Formatsmp4, mov, mkv, m4v, avi, gif

Examples: 3840×2160 = 8.3 MP ✅, 7680×4320 = 33.2 MP ✅, 8192×4608 = 37.7 MP ❌

For videos, resolution is required. Choose based on your needs:

  • Keep original size? Set resolution to original dimensions (use --original-resolution for better quality).
  • Upscale? Multiply original width/height by factor (2x, 4x).
  • Downscale? Rare but possible; just specify smaller dimensions.

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

平台分布

OpenClaw

92.61%
按下载量换算3,780

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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