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Agent Skill · 运维和基础设施

baoyu-imagine(宝玉想象)

baoyu-imagine 用于补充运维和基础设施相关能力,适合在 Local Agent 中需要让 Agent 承接运维和基础设施相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

baoyu-imagine 是运维和基础设施类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为接触敏感数据;许可证信息还不明确,暂无第三方扫描结果,按安装量在运维和基础设施类的 2,449 个 Skill 里排第 1,776。

总安装 399周安装 16下载 129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。
许可证
unknown

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:baoyu-imagine(宝玉想象)
来源仓库:https://skills.netease.im
仓库路径:baoyu-imagine
安装命令:
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。当前暂无明确安装命令,请以来源页面说明为准。

这个 Skill 是做什么的

运维和基础设施类 Skill 处理部署、监控、日志和云资源,多数需要较高的执行权限。

用于补充运维和基础设施相关能力。适合在 Local Agent 中让 Agent 承接运维和基础设施相关任务。通过未知方式安装,需结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

baoyu-imagine 属于运维和基础设施类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:baoyu-imagine

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 Local Agent;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

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 baoyu-imagine。

  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

baoyu-imagine 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 baoyu-imagine。

baoyu-imagine 支持哪些 AI 工具?

公开资料标注支持 Local Agent。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。

baoyu-imagine 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。

baoyu-imagine 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

baoyu-imagine 用的人多吗?

公开数据是累计安装 399 次,近一周安装 16 次,下载 129 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。

baoyu-imagine 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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 Local Agent,想直接扩展它能力的人。
  • 需要处理运维和基础设施类任务、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。
  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。

运维和基础设施类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
brainstorming

头脑风暴 · Codex、Claude

3,148,776173,131操作浏览器MIT通过
copywriting

文案写作 · Codex、Claude

1,996,72425,583需要联网MIT通过
openclaw-secure-linux-cloud

OpenClaw secure linux cloud 命令行 · Codex、Claude

1,853,08840接触敏感数据未明确未通过
xget

xget 命令行 · Codex、Claude

1,799,28040执行命令未明确未通过
requesting-code-review

代码审查请求 · Codex、Claude

1,590,144173,103权限未标注MIT通过
baoyu-imagine

宝玉想象 · 本页

399—接触敏感数据未明确未收录

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

Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.

Script Directory

Agent Execution:

  1. {baseDir} = this SKILL.md file's directory
  2. Script path = {baseDir}/scripts/main.ts
  3. Resolve ${BUN_X} runtime: if bun installed → bun; if npx available → npx -y bun; else suggest installing bun

Step 0: Load Preferences ⛔ BLOCKING

CRITICAL: This step MUST complete BEFORE any image generation. Do NOT skip or defer.

Check EXTEND.md existence (priority: project → user):

# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-imagine/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-imagine/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md" && echo "user"
# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-imagine/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-imagine/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md") { "user" }
ResultAction
FoundLoad, parse, apply settings. If default_model.[provider] is null → ask model only (Flow 2)
Not found⛔ Run first-time setup (references/config/first-time-setup.md) → Save EXTEND.md → Then continue

CRITICAL: If not found, complete the full setup (provider + model + quality + save location) using AskUserQuestion BEFORE generating any images. Generation is BLOCKED until EXTEND.md is created.

PathLocation
.baoyu-skills/baoyu-imagine/EXTEND.mdProject directory
$HOME/.baoyu-skills/baoyu-imagine/EXTEND.mdUser home

Legacy compatibility: if .baoyu-skills/baoyu-image-gen/EXTEND.md exists and the new path does not, runtime renames it to baoyu-imagine. If both files exist, runtime leaves them unchanged and uses the new path.

EXTEND.md Supports: Default provider | Default quality | Default aspect ratio | Default image size | Default models | Batch worker cap | Provider-specific batch limits

Schema: references/config/preferences-schema.md

Usage

# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png

# With aspect ratio
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9

# High quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k

# From prompt files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png

# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png

# With reference images (explicit provider/model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png

# Azure OpenAI (model means deployment name)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider azure --model gpt-image-1.5

# OpenRouter (recommended default model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openrouter

# OpenRouter with reference images
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png

# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai

# DashScope (阿里通义万象)
${BUN_X} {baseDir}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope

# DashScope Qwen-Image 2.0 Pro (recommended for custom sizes and text rendering)
${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9 横幅海报,包含清晰中文标题" --image out.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872

# DashScope legacy Qwen fixed-size model
${BUN_X} {baseDir}/scripts/main.ts --prompt "一张电影感海报" --image out.png --provider dashscope --model qwen-image-max --size 1664x928

# MiniMax
${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax

# MiniMax with subject reference (best for character/portrait consistency)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9

# MiniMax with custom size (documented for image-01)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic poster" --image out.jpg --provider minimax --model image-01 --size 1536x1024

# Replicate (google/nano-banana-pro)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate

# Replicate with specific model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana

# Batch mode with saved prompt files
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json

# Batch mode with explicit worker count
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json

Batch File Format

{
  "jobs": 4,
  "tasks": [
    {
      "id": "hero",
      "promptFiles": ["prompts/hero.md"],
      "image": "out/hero.png",
      "provider": "replicate",
      "model": "google/nano-banana-pro",
      "ar": "16:9",
      "quality": "2k"
    },
    {
      "id": "diagram",
      "promptFiles": ["prompts/diagram.md"],
      "image": "out/diagram.png",
      "ref": ["references/original.png"]
    }
  ]
}

Paths in promptFiles, image, and ref are resolved relative to the batch file's directory. jobs is optional (overridden by CLI --jobs). Top-level array format (without jobs wrapper) is also accepted.

Options

OptionDescription
--prompt <text>, -pPrompt text
--promptfiles <files...>Read prompt from files (concatenated)
--image <path>Output image path (required in single-image mode)
--batchfile <path>JSON batch file for multi-image generation
--jobs <count>Worker count for batch mode (default: auto, max from config, built-in default 10)
`--provider google\openai\azure\openrouter\dashscope\minimax\jimeng\seedream\replicate`Force provider (default: auto-detect)
--model <id>, -mModel ID (Google: gemini-3-pro-image-preview; OpenAI: gpt-image-1.5; Azure: deployment name such as gpt-image-1.5 or image-prod; OpenRouter: google/gemini-3.1-flash-image-preview; DashScope: qwen-image-2.0-pro; MiniMax: image-01)
--ar <ratio>Aspect ratio (e.g., 16:9, 1:1, 4:3)
--size <WxH>Size (e.g., 1024x1024)
`--quality normal\2k`Quality preset (default: 2k)
`--imageSize 1K\2K\4K`Image size for Google/OpenRouter (default: from quality)
--ref <files...>Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate, MiniMax subject-reference, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed SeedEdit 3.0
--n <count>Number of images
--jsonJSON output

Environment Variables

VariableDescription
OPENAI_API_KEYOpenAI API key
AZURE_OPENAI_API_KEYAzure OpenAI API key
OPENROUTER_API_KEYOpenRouter API key
GOOGLE_API_KEYGoogle API key
DASHSCOPE_API_KEYDashScope API key (阿里云)
MINIMAX_API_KEYMiniMax API key
REPLICATE_API_TOKENReplicate API token
JIMENG_ACCESS_KEY_IDJimeng (即梦) Volcengine access key
JIMENG_SECRET_ACCESS_KEYJimeng (即梦) Volcengine secret key
ARK_API_KEYSeedream (豆包) Volcengine ARK API key
OPENAI_IMAGE_MODELOpenAI model override
AZURE_OPENAI_DEPLOYMENTAzure default deployment name
AZURE_OPENAI_IMAGE_MODELBackward-compatible alias for Azure default deployment/model name
OPENROUTER_IMAGE_MODELOpenRouter model override (default: google/gemini-3.1-flash-image-preview)
GOOGLE_IMAGE_MODELGoogle model override
DASHSCOPE_IMAGE_MODELDashScope model override (default: qwen-image-2.0-pro)
MINIMAX_IMAGE_MODELMiniMax model override (default: image-01)
REPLICATE_IMAGE_MODELReplicate model override (default: google/nano-banana-pro)
JIMENG_IMAGE_MODELJimeng model override (default: jimeng_t2i_v40)
SEEDREAM_IMAGE_MODELSeedream model override (default: doubao-seedream-5-0-260128)
OPENAI_BASE_URLCustom OpenAI endpoint
AZURE_OPENAI_BASE_URLAzure resource endpoint or deployment endpoint
AZURE_API_VERSIONAzure image API version (default: 2025-04-01-preview)
OPENROUTER_BASE_URLCustom OpenRouter endpoint (default: https://openrouter.ai/api/v1)
OPENROUTER_HTTP_REFEREROptional app/site URL for OpenRouter attribution
OPENROUTER_TITLEOptional app name for OpenRouter attribution
GOOGLE_BASE_URLCustom Google endpoint
DASHSCOPE_BASE_URLCustom DashScope endpoint
MINIMAX_BASE_URLCustom MiniMax endpoint (default: https://api.minimax.io)
REPLICATE_BASE_URLCustom Replicate endpoint
JIMENG_BASE_URLCustom Jimeng endpoint (default: https://visual.volcengineapi.com)
JIMENG_REGIONJimeng region (default: cn-north-1)
SEEDREAM_BASE_URLCustom Seedream endpoint (default: https://ark.cn-beijing.volces.com/api/v3)
BAOYU_IMAGE_GEN_MAX_WORKERSOverride batch worker cap
BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCYOverride provider concurrency, e.g. BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY
BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MSOverride provider start gap, e.g. BAOYU_IMAGE_GEN_REPLICATE_START_INTERVAL_MS

Load Priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env

Model Resolution

Model priority (highest → lowest), applies to all providers:

  1. CLI flag: --model <id>
  2. EXTEND.md: default_model.[provider]
  3. Env var: <PROVIDER>_IMAGE_MODEL (e.g., GOOGLE_IMAGE_MODEL)
  4. Built-in default

For Azure, --model / default_model.azure should be the Azure deployment name. AZURE_OPENAI_DEPLOYMENT is the preferred env var, and AZURE_OPENAI_IMAGE_MODEL remains as a backward-compatible alias.

EXTEND.md overrides env vars. If both EXTEND.md default_model.google: "gemini-3-pro-image-preview" and env var GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview exist, EXTEND.md wins.

Agent MUST display model info before each generation:

  • Show: Using [provider] / [model]
  • Show switch hint: Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL

DashScope Models

Use --model qwen-image-2.0-pro or set default_model.dashscope / DASHSCOPE_IMAGE_MODEL when the user wants official Qwen-Image behavior.

Official DashScope model families:

  • qwen-image-2.0-pro, qwen-image-2.0-pro-2026-03-03, qwen-image-2.0, qwen-image-2.0-2026-03-03

- Free-form size in 宽*高 format - Total pixels must stay between 512*512 and 2048*2048 - Default size is approximately 1024*1024 - Best choice for custom ratios such as 21:9 and text-heavy Chinese/English layouts

  • qwen-image-max, qwen-image-max-2025-12-30, qwen-image-plus, qwen-image-plus-2026-01-09, qwen-image

- Fixed sizes only: 1664*928, 1472*1104, 1328*1328, 1104*1472, 928*1664 - Default size is 1664*928 - qwen-image currently has the same capability as qwen-image-plus

  • Legacy DashScope models such as z-image-turbo, z-image-ultra, wanx-v1

- Keep using them only when the user explicitly asks for legacy behavior or compatibility

When translating CLI args into DashScope behavior:

  • --size wins over --ar
  • For qwen-image-2.0*, prefer explicit --size; otherwise infer from --ar and use the official recommended resolutions below
  • For qwen-image-max/plus/image, only use the five official fixed sizes; if the requested ratio is not covered, switch to qwen-image-2.0-pro
  • --quality is a baoyu-imagine compatibility preset, not a native DashScope API field. Mapping normal / 2k onto the qwen-image-2.0* table below is an implementation inference, not an official API guarantee

Recommended qwen-image-2.0* sizes for common aspect ratios:

Rationormal2k
1:11024*10241536*1536
2:3768*11521024*1536
3:21152*7681536*1024
3:4960*12801080*1440
4:31280*9601440*1080
9:16720*12801080*1920
16:91280*7201920*1080
21:91344*5762048*872

DashScope official APIs also expose negative_prompt, prompt_extend, and watermark, but baoyu-imagine does not expose them as dedicated CLI flags today.

Official references:

MiniMax Models

Use --model image-01 or set default_model.minimax / MINIMAX_IMAGE_MODEL when the user wants MiniMax image generation.

Official MiniMax image model options currently documented in the API reference:

  • image-01 (recommended default)

- Supports text-to-image and subject-reference image generation - Supports official aspect_ratio values: 1:1, 16:9, 4:3, 3:2, 2:3, 3:4, 9:16, 21:9 - Supports documented custom width / height output sizes when using --size <WxH> - width and height must both be between 512 and 2048, and both must be divisible by 8

  • image-01-live

- Lower-latency variant - Use --ar for sizing; MiniMax documents custom width / height as only effective for image-01

MiniMax subject reference notes:

  • --ref files are sent as MiniMax subject_reference
  • MiniMax docs currently describe subject_reference[].type as character
  • Official docs say image_file supports public URLs or Base64 Data URLs; baoyu-imagine sends local refs as Data URLs
  • Official docs recommend front-facing portrait references in JPG/JPEG/PNG under 10MB

Official references:

OpenRouter Models

Use full OpenRouter model IDs, e.g.:

  • google/gemini-3.1-flash-image-preview (recommended, supports image output and reference-image workflows)
  • google/gemini-2.5-flash-image-preview
  • black-forest-labs/flux.2-pro
  • Other OpenRouter image-capable model IDs

Notes:

  • OpenRouter image generation uses /chat/completions, not the OpenAI /images endpoints
  • If --ref is used, choose a multimodal model that supports image input and image output
  • --imageSize maps to OpenRouter imageGenerationOptions.size; --size <WxH> is converted to the nearest OpenRouter size and inferred aspect ratio when possible

Replicate Models

Supported model formats:

  • owner/name (recommended for official models), e.g. google/nano-banana-pro
  • owner/name:version (community models by version), e.g. stability-ai/sdxl:<version>

Examples:

# Use Replicate default model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate

# Override model explicitly
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana

Provider Selection

  1. --ref provided + no --provider → auto-select Google first, then OpenAI, then Azure, then OpenRouter, then Replicate, then Seedream, then MiniMax (MiniMax subject reference is more specialized toward character/portrait consistency)
  2. --provider specified → use it (if --ref, must be google, openai, azure, openrouter, replicate, seedream, or minimax)
  3. Only one API key available → use that provider
  4. Multiple available → default to Google

Quality Presets

PresetGoogle imageSizeOpenAI SizeOpenRouter sizeReplicate resolutionUse Case
normal1K1024px1K1KQuick previews
2k (default)2K2048px2K2KCovers, illustrations, infographics

Google/OpenRouter imageSize: Can be overridden with --imageSize 1K|2K|4K

Aspect Ratios

Supported: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1

  • Google multimodal: uses imageConfig.aspectRatio
  • OpenAI: maps to closest supported size
  • OpenRouter: sends imageGenerationOptions.aspect_ratio; if only --size <WxH> is given, aspect ratio is inferred automatically
  • Replicate: passes aspect_ratio to model; when --ref is provided without --ar, defaults to match_input_image
  • MiniMax: sends official aspect_ratio values directly; if --size <WxH> is given without --ar, width / height are sent for image-01

Generation Mode

Default: Sequential generation.

Batch Parallel Generation: When --batchfile contains 2 or more pending tasks, the script automatically enables parallel generation.

ModeWhen to Use
Sequential (default)Normal usage, single images, small batches
Parallel batchBatch mode with 2+ tasks

Execution choice:

SituationPreferred approachWhy
One image, or 1-2 simple imagesSequentialLower coordination overhead and easier debugging
Multiple images already have saved prompt filesBatch (--batchfile)Reuses finalized prompts, applies shared throttling/retries, and gives predictable throughput
Each image still needs separate reasoning, prompt writing, or style explorationSubagentsThe work is still exploratory, so each image may need independent analysis before generation
Output comes from baoyu-article-illustrator with outline.md + prompts/Batch (build-batch.ts -> --batchfile)That workflow already produces prompt files, so direct batch execution is the intended path

Rule of thumb:

  • Prefer batch over subagents once prompt files are already saved and the task is "generate all of these"
  • Use subagents only when generation is coupled with per-image thinking, rewriting, or divergent creative exploration

Parallel behavior:

  • Default worker count is automatic, capped by config, built-in default 10
  • Provider-specific throttling is applied only in batch mode, and the built-in defaults are tuned for faster throughput while still avoiding obvious RPM bursts
  • You can override worker count with --jobs <count>
  • Each image retries automatically up to 3 attempts
  • Final output includes success count, failure count, and per-image failure reasons

Error Handling

  • Missing API key → error with setup instructions
  • Generation failure → auto-retry up to 3 attempts per image
  • Invalid aspect ratio → warning, proceed with default
  • Reference images with unsupported provider/model → error with fix hint

Extension Support

Custom configurations via EXTEND.md. See Preferences section for paths and supported options.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

Local Agent

71.74%
按下载量换算93

安全审计

暂无安全审计结果可展示。

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。目前只有一个公开来源,建议同时核对源仓库。

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