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Agent Skill · 效率

test-security(测试安全性)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

test-security 是效率类 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,按安装量在效率类的 21,003 个 Skill 里排第 16,384。

总安装 2,880周安装 120GitHub Stars 公开资料未说明下载 960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
1.0.0

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:test-security(测试安全性)
来源仓库:https://github.com/levdavid1/test-security
安装命令:
openclaw skills install test-security
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 test-security

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

test-security 用于图像背景去除与 AI 生成,由 RMBG-2.0 模型提供支持。适合产品摄影与广告设计,输出透明 PNG 文件。支持商业用途,但需遵守 API 使用条款与授权范围。安装命令为 openclaw skills install test-security,需完成 OAuth 设备流认证。

建议缓存凭据于本地,避免重复登录操作。

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 test-security;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

test-security 怎么安装?

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

test-security 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。

test-security 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。

test-security 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。

test-security 用的人多吗?

公开数据是累计安装 2,880 次,近一周安装 120 次,下载 960 次。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。

test-security 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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
test-security

测试安全性 · 本页

2,880—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
bria-ai
description
AI image generation, editing, and background removal API via Bria.ai — remove backgrounds to get transparent PNGs and cutouts, generate images from text prompts, and edit photos with natural language instructions. Also create product photography and lifestyle shots, replace or blur backgrounds, upscale resolution, restyle, and batch-generate visual assets. Use this skill whenever the user wants to remove a background, create transparent PNGs, generate, edit, modify, or transform any image — including hero images, banners, social media visuals, product photos, illustrations, icons, thumbnails, ad creatives, or marketing materials. Also triggers on cutout, inpainting, outpainting, object removal or addition, photo restoration, style transfer, image enhancement, relight, reseason, sketch-to-photo, or any visual content creation. Commercially safe, royalty-free. 20+ specialized endpoints for e-commerce, web design, and content pipelines.
license
MIT
metadata
author
Bria AI
version
1.2.7

Bria — AI Image Generation, Editing & Background Removal

Commercially safe, royalty-free image generation and editing through 20+ API endpoints. Generate from text, edit with natural language, remove backgrounds, create product shots, and build automated image pipelines.

If you are stuck on request shapes, parameters, or endpoints not covered here, fetch the full agent-oriented API reference at docs.bria.ai/llms.txt — it is the canonical LLM-ready documentation and the right place to look before guessing.

When to Use This Skill

Use this skill when the user wants to:

  • Generate images — "create an image of...", "make me a banner", "generate a hero image", "I need a product photo"
  • Edit images — "change the background", "make it look like winter", "add a vase to the table", "remove the person"
  • Remove/replace backgrounds — "make the background transparent", "cut out the product", "replace with a studio background"
  • Product photography — "create a lifestyle shot", "place this product in a kitchen scene", "e-commerce packshot"
  • Enhance/transform — "upscale this image", "make it higher resolution", "restyle as oil painting", "change the lighting"
  • Batch/pipeline — "generate 10 product images", "process all these images", "remove backgrounds in bulk"

This skill handles the full spectrum of AI image operations. If the user mentions images, photos, visuals, or any visual content creation — use this skill.


What You Can Build

  • E-commerce product catalog — Generate product photos, remove backgrounds for transparent PNGs, place products in lifestyle scenes (kitchen, office, outdoor), create packshots with consistent style
  • Landing page visuals — Generate hero images, abstract tech backgrounds, team photos, and section illustrations — all matching your brand aesthetic
  • Social media content — Instagram posts (1:1), Stories/Reels (9:16), LinkedIn banners (16:9), ad creatives — batch-generate variants for A/B testing
  • Marketing campaign assets — Seasonal transformations (summer→winter), restyle product shots for different markets, create localized visuals at scale
  • Photo restoration pipeline — Restore old damaged photos, colorize black & white images, upscale low-res photos to 4x, enhance quality automatically
  • Brand asset toolkit — Remove backgrounds from logos, blend artwork onto products (t-shirts, mugs), create consistent product photography across your entire catalog
  • AI-powered design workflows — Chain operations: generate→edit→remove background→place in scene→upscale — all automated through API pipelines

Setup — Authentication

Before making any API call, you need a valid Bria access token.

Step 1: Check for existing credentials

if [ -f ~/.bria/credentials ]; then
  BRIA_ACCESS_TOKEN=$(grep '^access_token=' "$HOME/.bria/credentials" | cut -d= -f2-)
  BRIA_API_KEY=$(grep '^api_token=' "$HOME/.bria/credentials" | cut -d= -f2-)
fi
if [ -z "$BRIA_ACCESS_TOKEN" ]; then
  echo "NO_CREDENTIALS"
elif [ -n "$BRIA_API_KEY" ]; then
  echo "READY"
else
  echo "CREDENTIALS_FOUND"
fi

If the output is READY, skip straight to making API calls — no introspection needed. If the output is CREDENTIALS_FOUND, skip to Step 3. If the output is NO_CREDENTIALS, proceed to Step 2.

Step 2: Authenticate via device authorization

Start the device authorization flow:

2a. Request a device code:

DEVICE_RESPONSE=$(curl -s -X POST "https://engine.prod.bria-api.com/v2/auth/device/authorize" \
  -H "Content-Type: application/json")
echo "$DEVICE_RESPONSE"

Parse the response fields:

  • device_code — used to poll for the token (keep this, don't show to user)
  • user_code — the code the user must enter (e.g. BRIA-XXXX)
  • interval — seconds between poll attempts

2b. Show the user a single sign-in link. Tell them exactly this — nothing more:

Connect your Bria account: Click here to sign in Your code is {user_code} — it's already filled in.

Do NOT show two links. Do NOT show the raw URL separately. Do NOT use verification_uri from the API response. Keep it to one clickable link.

2c. Poll for the token. After showing the user the code, immediately start polling. Try up to 60 times with the given interval (default 5 seconds):

for i in $(seq 1 60); do
  TOKEN_RESPONSE=$(curl -s -X POST "https://engine.prod.bria-api.com/v2/auth/token" \
    -d "grant_type=urn:ietf:params:oauth:grant-type:device_code" \
    -d "device_code=$DEVICE_CODE")
  ACCESS_TOKEN=$(printf '%s' "$TOKEN_RESPONSE" | sed -n 's/.*"access_token" *: *"\([^"]*\)".*/\1/p')
  if [ -n "$ACCESS_TOKEN" ]; then
    BRIA_ACCESS_TOKEN="$ACCESS_TOKEN"
    REFRESH_TOKEN=$(printf '%s' "$TOKEN_RESPONSE" | sed -n 's/.*"refresh_token" *: *"\([^"]*\)".*/\1/p')
    mkdir -p ~/.bria
    printf 'access_token=%s\
refresh_token=%s\
' "$BRIA_ACCESS_TOKEN" "$REFRESH_TOKEN" > "$HOME/.bria/credentials"
    echo "AUTHENTICATED"
    break
  fi
  sleep 5
done

If the output contains AUTHENTICATED, proceed to Step 3. Otherwise the code expired — start over from Step 2a.

Do not proceed with any API call until authentication is confirmed.

Step 3: Verify billing status and resolve API key

Introspect the bearer token to check billing status and obtain the real API key for Bria API calls:

INTROSPECT=$(curl -s -X POST "https://engine.prod.bria-api.com/v2/auth/token/introspect" \
  -d "token=$BRIA_ACCESS_TOKEN")
BILLING_STATUS=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"billing_status" *: *"\([^"]*\)".*/\1/p')
if [ "$BILLING_STATUS" = "blocked" ]; then
  BILLING_MSG=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"billing_message" *: *"\([^"]*\)".*/\1/p')
  echo "BILLING_ERROR: $BILLING_MSG"
fi
ACTIVE=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"active" *: *\([^,}]*\).*/\1/p' | tr -d ' ')
if [ "$ACTIVE" = "false" ]; then
  rm -f ~/.bria/credentials
  echo "TOKEN_EXPIRED"
fi
BRIA_API_KEY=$(printf '%s' "$INTROSPECT" | sed -n 's/.*"api_token" *: *"\([^"]*\)".*/\1/p')
if [ -n "$BRIA_API_KEY" ]; then
  grep -v '^api_token=' "$HOME/.bria/credentials" > "$HOME/.bria/credentials.tmp" 2>/dev/null || true
  printf 'api_token=%s\
' "$BRIA_API_KEY" >> "$HOME/.bria/credentials.tmp"
  mv "$HOME/.bria/credentials.tmp" "$HOME/.bria/credentials"
fi

Interpret the output:

  • If it prints BILLING_ERROR: ... — relay the message to the user exactly as shown and stop. Do not make any API calls.
  • If it prints TOKEN_EXPIRED — the session is no longer valid. Tell the user their session expired and restart from Step 2.
  • Otherwise, BRIA_API_KEY now contains the real API key and is cached for future calls. Proceed to the next section.

Core Capabilities

NeedCapabilityUse Case
Generate images from textFIBO GenerateHero images, product shots, illustrations, social media images, banners
Edit images by text instructionFIBO-EditChange colors, modify objects, transform scenes
Edit image region with maskGenFill/ErasePrecise inpainting, add/replace specific regions
Add/Replace/Remove objectsText-based editingAdd vase, replace apple with pear, remove table
Remove background (transparent PNG)RMBG-2.0Extract subjects for overlays, logos, cutouts
Replace/blur/erase backgroundBackground opsChange, blur, or remove backgrounds
Expand/outpaint imagesOutpaintingExtend boundaries, change aspect ratios
Upscale image resolutionSuper ResolutionIncrease resolution 2x or 4x
Enhance image qualityEnhancementImprove lighting, colors, details
Restyle imagesRestyleOil painting, anime, cartoon, 3D render
Change lightingRelightGolden hour, spotlight, dramatic lighting
Change seasonReseasonSpring, summer, autumn, winter
Composite/blend imagesImage BlendingApply textures, logos, merge images
Restore old photosRestorationFix old/damaged photos
Colorize imagesColorizationAdd color to B&W, or convert to B&W
Sketch to photoSketch2ImageConvert drawings to realistic photos
Create product lifestyle shotsLifestyle ShotPlace products in scenes for e-commerce
Integrate products into scenesProduct IntegrateEmbed products at exact coordinates

How to Call Any Endpoint

Use bria_call for all API calls. It handles URL passthrough, local file base64 encoding, JSON construction, API call, and async polling in a single function call. The API key is auto-loaded from ~/.bria/credentials.

source ~/.agents/skills/bria-ai/references/code-examples/bria_client.sh

# Generate (no image input — pass empty string)
RESULT=$(bria_call /v2/image/generate "" '"prompt": "your description", "aspect_ratio": "16:9", "sync": true')

# Remove background
RESULT=$(bria_call /v2/image/edit/remove_background "/path/to/local/image.png")

# Replace background
RESULT=$(bria_call /v2/image/edit/replace_background "https://example.com/img.jpg" '"prompt": "sunset beach"')

# Edit image (uses images array — pass --key images)
RESULT=$(bria_call /v2/image/edit "/path/to/image.png" --key images '"instruction": "make it look warmer"')

# Upscale
RESULT=$(bria_call /v2/image/edit/increase_resolution "https://example.com/img.jpg" '"scale": 4')

# Lifestyle shot
RESULT=$(bria_call /v1/product/lifestyle_shot_by_text "/path/to/product.png" '"prompt": "modern kitchen countertop"')

echo "$RESULT"

Calling convention: bria_call <endpoint> <image_or_empty> [--key <json_key>] [extra JSON fields...]

  • Pass a URL, local file path, or "" (empty) for endpoints without image input
  • Use --key images when the endpoint expects an images array instead of image
  • Extra JSON fields are appended as key-value pairs: '"key": "value"'
  • Returns the result image URL on success, or prints an error to stderr

Generation options: Aspect ratios 1:1, 16:9, 4:3, 9:16, 3:4. Resolution 1MP (default) or 4MP (more detail, +30s). Pass "sync": true for single images.

Advanced: For precise control over generation, use VGL structured prompts instead of natural language.

See API Endpoints Reference for full parameter documentation on all 20+ endpoints.


Prompt Engineering Tips

  • Style: "professional product photography" vs "casual snapshot", "flat design illustration" vs "3D rendered"
  • Lighting: "soft natural light", "studio lighting", "dramatic shadows"
  • Background: "white studio", "gradient", "blurred office", "transparent"
  • Composition: "centered", "rule of thirds", "negative space on left for text"
  • Quality keywords: "high quality", "professional", "commercial grade", "4K", "sharp focus"
  • Negative prompts: "blurry, low quality, pixelated", "text, watermark, logo"

Recipes by Use Case

Hero banner (16:9): "Modern tech startup workspace with developers collaborating, bright natural lighting, clean minimal aesthetic" — include "clean background" or "minimal" for text overlay space

Product photo (1:1): "Professional product photo of [item] on white studio background, soft shadows, commercial photography lighting" — then remove background for transparent PNG

Presentation visual (16:9): "Abstract visualization of data analytics, blue and purple gradient, modern corporate style, clean composition with space for text" — common themes: "abstract technology", "business collaboration", "minimalist geometric patterns"

Instagram post (1:1): "Lifestyle photo of coffee and laptop on wooden desk, morning light, cozy atmosphere"

Story/Reel (9:16): "Vertical product showcase of smartphone, floating in gradient background, tech aesthetic"


Additional Resources

Related Skills

  • vgl — Write structured VGL JSON prompts for precise, deterministic control over FIBO image generation
  • image-utils — Classic image manipulation (resize, crop, composite, watermarks) for post-processing

适合场景

01

商品图处理

02

人像抠图

03

透明背景素材

04

营销设计资产

能力概览

能力 1

调用背景移除模型

能力 2

输出透明背景图片

能力 3

支持商品、人像和营销素材处理

能力 4

可接入图像编辑工作流

平台分布

OpenClaw

70.97%
按下载量换算681

安全审计

VirusTotal

通过

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。

继续浏览同类 Skills