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Agent Skill · 图像处理

baoyu-image-cards(宝玉形象卡)

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。

baoyu-image-cards 是图像处理类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在图像处理类的 1,562 个 Skill 里排第 58。

总安装 62,856周安装 2,673GitHub Stars 16,768下载 22,032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
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-image-cards(宝玉形象卡)
来源仓库:https://github.com/jimliu/baoyu-skills
仓库路径:skills/baoyu-image-cards
安装命令:
npx skills add https://github.com/jimliu/baoyu-skills --skill baoyu-image-cards
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/jimliu/baoyu-skills --skill baoyu-image-cards

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、图片编辑、视觉素材处理或图像模型工作流。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。

建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/baoyu-image-cards

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/jimliu/baoyu-skills --skill baoyu-image-cards;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

baoyu-image-cards 怎么安装?

在终端执行 npx skills add https://github.com/jimliu/baoyu-skills --skill baoyu-image-cards。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

baoyu-image-cards 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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-image-cards 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

baoyu-image-cards 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-image-cards 用的人多吗?

公开数据是累计安装 62,856 次,近一周安装 2,673 次,下载 22,032 次,GitHub 16,768 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。

baoyu-image-cards 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 16,768 星,维护活跃度相对可查。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
baoyu-image-cards

宝玉形象卡 · 本页

62,85616,768只读未明确通过

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 Card Series Generator

Break down complex content into eye-catching image card series with multiple style options.

User Input Tools

When this skill prompts the user, follow this tool-selection rule (priority order):

  1. Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.
  2. Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
  3. Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.

Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.

Image Generation Tools

When this skill needs to render an image, resolve the backend in this order:

  1. Current-request override — if the user names a specific backend in the current message, use it.
  2. Saved preference — if EXTEND.md sets preferred_image_backend to a backend available right now, use it.
  3. Auto-select (when the preference is auto, unset, or the pinned backend isn't available):

- If the current runtime exposes a native image tool (e.g., Codex imagegen, Hermes image_generate), use it. Runtime-native tools are preferred by default — agents that know their own tool inventory should surface the native one here. - Otherwise, if exactly one non-native backend is installed (e.g., baoyu-imagine), use it. - Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions.

  1. If none are available, tell the user and ask how to proceed.

Setting preferred_image_backend: ask forces the step-3 prompt every run regardless of available backends. Users change the pinned backend via the ## Changing Preferences section below.

Prompt file requirement (hard): write each image's full, final prompt to a standalone file under prompts/ (naming: NN-{type}-[slug].md) BEFORE invoking any backend. The file is the reproducibility record and lets you switch backends without regenerating prompts.

Concrete tool names (imagegen, image_generate, baoyu-imagine) above are examples — substitute the local equivalents under the same rule.

Confirmation Policy

Default behavior: confirm before generation.

  • Treat explicit skill invocation, a file path, matched signals/presets, and EXTEND.md defaults as recommendation inputs only. None of them authorizes skipping confirmation.
  • Do not start Step 3 until the user completes Step 2.
  • Skip confirmation only when the current request explicitly says to do so, for example: --yes, "直接生成", "不用确认", "跳过确认", "按默认出图", or equivalent wording.
  • If confirmation is skipped explicitly, state the assumed strategy / style / layout / palette / count / backend in the next user-facing update before generating.

Language

Respond in the user's language across questions, progress, errors, and completion summary. Keep technical tokens (style names, file paths, code) in English.

Options

OptionDescription
--style <name>Visual style (see Styles below)
--layout <name>Information layout (see Layouts below)
--palette <name>Color override: macaron / warm / neon
--preset <name>Style + layout + optional palette shorthand (see Presets below; per-preset prompt fragments in references/style-presets.md)
--ref <files...>Reference images applied to image 1 as the series anchor
--yesNon-interactive: skip all confirmations, use EXTEND.md or built-in defaults, auto-confirm recommended plan (Path A)

Dimensions

Three independent knobs combine freely:

DimensionControlsOptions
StyleVisual aesthetics (lines, decorations, rendering)12 styles (see Styles below)
LayoutInformation structure (density, arrangement)8 layouts (see Layouts below)
Palette (optional)Color override, replaces the style's default colorsmacaron / warm / neon (see Palettes below)

Example: --style notion --layout dense makes an intellectual knowledge card; add --palette macaron to soften the colors without changing notion's rendering rules. A --preset is a shorthand for style + layout (+ optional palette).

Palette behavior: no --palette → style's built-in colors; --palette <name> → overrides colors only, rendering rules unchanged. Some styles declare a default_palette (e.g., sketch-notes defaults to macaron).

Styles (12)

StyleDescription
cute (Default)Sweet, adorable, girly aesthetic
freshClean, refreshing, natural
warmCozy, friendly, approachable
boldHigh impact, attention-grabbing
minimalUltra-clean, sophisticated
retroVintage, nostalgic, trendy
popVibrant, energetic, eye-catching
notionMinimalist hand-drawn line art, intellectual
chalkboardColorful chalk on black board, educational
study-notesRealistic handwritten photo style, blue pen + red annotations + yellow highlighter
screen-printBold poster art, halftone textures, limited colors, symbolic storytelling
sketch-notesHand-drawn educational infographic, macaron pastels on warm cream, wobble lines

Per-style specifications: references/presets/<style>.md.

Layouts (8)

LayoutDescription
sparse (Default)1-2 points, maximum impact
balanced3-4 points, standard
dense5-8 points, knowledge-card style
listEnumeration / ranking (4-7 items)
comparisonSide-by-side contrast
flowProcess / timeline (3-6 steps)
mindmapCenter-radial (4-8 branches)
quadrantFour-quadrant / circular sections

Layout specs: references/elements/canvas.md.

Palettes (optional override)

Replaces the style's colors while keeping rendering rules (line treatment, textures) intact.

PaletteBackgroundZone ColorsAccentFeel
macaronWarm cream #F5F0E8Blue #A8D8EA, Lavender #D5C6E0, Mint #B5E5CF, Peach #F8D5C4Coral #E8655ASoft, educational
warmSoft peach #FFECD2Orange #ED8936, Terracotta #C05621, Golden #F6AD55, Rose #D4A09ASienna #A0522DEarth tones, cozy
neonDark purple #1A1025Cyan #00F5FF, Magenta #FF00FF, Green #39FF14, Pink #FF6EC7Yellow #FFFF00High-energy, futuristic

Palette specs: references/palettes/<palette>.md.

Presets (style + layout shortcuts)

Quick-start combos, grouped by scenario. Use --preset <name> or recommend during Step 2.

Knowledge & Learning:

PresetStyleLayoutBest For
knowledge-cardnotiondense干货知识卡、概念科普
checklistnotionlist清单、排行榜
concept-mapnotionmindmap概念图、知识脉络
swotnotionquadrantSWOT 分析、四象限
tutorialchalkboardflow教程步骤、操作流程
classroomchalkboardbalanced课堂笔记、知识讲解
study-guidestudy-notesdense学习笔记、考试重点
hand-drawn-edusketch-notesflow手绘教程、流程图解
sketch-cardsketch-notesdense手绘知识卡
sketch-summarysketch-notesbalanced手绘总结、图文笔记

Lifestyle & Sharing:

PresetStyleLayoutBest For
cute-sharecutebalanced少女风分享、日常种草
girlycutesparse甜美封面、氛围感
cozy-storywarmbalanced生活故事、情感分享
product-reviewfreshcomparison产品对比、测评
nature-flowfreshflow健康流程、自然主题

Impact & Opinion:

PresetStyleLayoutBest For
warningboldlist避坑指南、重要提醒
versusboldcomparison正反对比
clean-quoteminimalsparse金句、极简封面
pro-summaryminimalbalanced专业总结、商务内容

Trend & Entertainment:

PresetStyleLayoutBest For
retro-rankingretrolist复古排行、经典盘点
throwbackretrobalanced怀旧分享
pop-factspoplist趣味冷知识
hypepopsparse炸裂封面、惊叹分享

Poster & Editorial:

PresetStyleLayoutBest For
posterscreen-printsparse海报风封面、影评书评
editorialscreen-printbalanced观点文章、文化评论
cinematicscreen-printcomparison电影对比、戏剧张力

Full prompt-fragment definitions: references/style-presets.md.

Auto-Selection

Match content signals to the best combo. First row whose keywords appear wins; fall back to cute-share if nothing matches.

Signals in sourceStyleLayoutRecommended preset
beauty, fashion, cute, girl, pinkcutesparse/balancedcute-share, girly
health, nature, fresh, organicfreshbalanced/flowproduct-review, nature-flow
life, story, emotion, warmwarmbalancedcozy-story
warning, important, must, criticalboldlist/comparisonwarning, versus
professional, business, elegantminimalsparse/balancedclean-quote, pro-summary
classic, vintage, traditionalretrobalancedthrowback, retro-ranking
fun, exciting, wow, amazingpopsparse/listhype, pop-facts
knowledge, concept, productivity, SaaSnotiondense/listknowledge-card, checklist
education, tutorial, learning, classroomchalkboardbalanced/densetutorial, classroom
notes, handwritten, study guide, realisticstudy-notesdense/list/mindmapstudy-guide
movie, poster, opinion, editorial, cinematicscreen-printsparse/comparisonposter, editorial, cinematic
hand-drawn, infographic, workflow, 手绘, 图解sketch-notesflow/balanced/densehand-drawn-edu, sketch-card, sketch-summary

Style × Layout Matrix

Compatibility scores (✓✓ highly recommended, ✓ works well, ✗ avoid). Use when the user picks a non-default combo and you want to flag a poor match.

sparsebalanceddenselistcomparisonflowmindmapquadrant
cute✓✓✓✓✓✓✓✓✓✓✓
fresh✓✓✓✓✓✓✓✓✓✓✓
warm✓✓✓✓✓✓✓✓✓✓✓
bold✓✓✓✓✓✓✓✓✓✓✓✓
minimal✓✓✓✓✓✓✓✓✓✓✓
retro✓✓✓✓✓✓✓✓✓✓✓
pop✓✓✓✓✓✓✓✓✓✓✓✓
notion✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓
chalkboard✓✓✓✓✓✓✓✓✓✓✓✓✓✓
study-notes✗✓✓✓✓✓✓✓✓✓✓
screen-print✓✓✓✓✗✓✓✓✓✗✓✓
sketch-notes✓✓✓✓✓✓✓✓✓✓✓✓✓

Outline Strategies

Three differentiated approaches — each produces a structurally different outline. The workflow recommends one; Path C generates all three and lets the user choose.

StrategyConceptBest forStructure
A — Story-DrivenPersonal experience as the thread, emotional resonance firstReviews, personal shares, transformationHook → Problem → Discovery → Experience → Conclusion
B — Information-DenseValue-first, efficient information deliveryTutorials, comparisons, checklistsCore conclusion → Info card → Pros/Cons → Recommendation
C — Visual-FirstVisual impact as core, minimal textHigh-aesthetic products, lifestyle, mood contentHero image → Detail shots → Lifestyle scene → CTA

Reference Images

User-supplied refs are separate from the internal "image-1 as anchor" chain (Step 3) — they layer on top of it.

Intake: via --ref <files...> or paths pasted in conversation.

  • File path → copy to refs/NN-ref-{slug}.{ext}
  • Pasted with no path → ask for the path, or extract style traits as a text fallback

Usage modes (per reference):

UsageEffect
directPass the file to the backend (typically on image 1 only, so the anchor propagates through the chain)
styleExtract style traits and append to every card's prompt body
paletteExtract hex colors and append to every card's prompt body

Record refs in each affected card's prompt frontmatter:

references:
  - ref_id: 01
    filename: 01-ref-brand.png
    usage: direct

At generation time: verify files exist. Image 1 with usage: direct + backend that accepts refs → pass via the backend's ref parameter (becomes the chain anchor). Images 2+ keep using image-1 as --ref per Step 3 — do NOT re-stack user refs on top (avoids conflicting signals). For style/palette, embed extracted traits in every prompt.

File Layout

image-cards/{topic-slug}/
├── source-{slug}.{ext}
├── analysis.md
├── outline-strategy-{a,b,c}.md    # Path C only
├── outline.md
├── prompts/NN-{type}-{slug}.md
├── NN-{type}-{slug}.png
└── refs/                          # only if --ref used

Slug: 2-4 words, kebab-case. "AI 工具推荐" → ai-tools-recommend. On collision, append -YYYYMMDD-HHMMSS.

Backup rule (applies throughout): before overwriting any file — source, outline, prompt, image — rename the existing one to <name>-backup-YYYYMMDD-HHMMSS.<ext>. This protects user edits.

Workflow

- [ ] Step 0: Load EXTEND.md ⛔ BLOCKING (interactive only)
- [ ] Step 1: Analyze content → analysis.md
- [ ] Step 2: Smart Confirm ⚠️ REQUIRED (Path A / B / C)
- [ ] Step 3: Generate images
- [ ] Step 4: Completion report

Step 0: Load EXTEND.md ⛔ BLOCKING

Check these paths in order; first hit wins:

PathScope
.baoyu-skills/baoyu-image-cards/EXTEND.mdProject
${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-cards/EXTEND.mdXDG
$HOME/.baoyu-skills/baoyu-image-cards/EXTEND.mdUser home
  • Found → read, parse, print a summary (style / layout / watermark / language), continue.
  • Not found + interactive → run first-time setup (see references/config/first-time-setup.md) and save before anything else. Do NOT analyze content or ask style questions until preferences exist — this keeps first-run behavior predictable.
  • Not found + --yes → skip setup, use built-in defaults (no watermark, style/layout auto-selected, language from content). Do not prompt, do not create EXTEND.md.

EXTEND.md keys: watermark, preferred style/layout, custom style definitions, language preference. Schema: references/config/preferences-schema.md.

Step 1: Analyze Content → analysis.md

  1. Save the source (backup rule applies if source.md exists).
  2. Run the deep analysis in references/workflows/analysis-framework.md: content type, hook potential, audience, engagement signals, visual opportunity map, swipe flow.
  3. Detect source language, pick recommended image count (2-10).
  4. Auto-recommend strategy + style + layout + palette using the Auto-Selection table above.
  5. Write everything to analysis.md.

Step 2: Smart Confirm ⚠️ REQUIRED

Hard gate: this step is mandatory per the Confirmation Policy — Step 3 cannot start until the user confirms here (or explicitly opts out with --yes / equivalent wording in the current request).

Goal: present the auto-recommended plan and let the user confirm or adjust. Skip this step entirely under --yes — proceed with Path A using the analysis and any CLI overrides.

Display summary before asking:

📋 内容分析
  主题:[topic] | 类型:[content_type]
  要点:[key points]
  受众:[audience]

🎨 推荐方案(自动匹配)
  策略:[A/B/C] [name]([reason])
  风格:[style] · 布局:[layout] · 配色:[palette or 默认] · 预设:[preset]
  图片:[N]张(封面+[N-2]内容+结尾)
  元素:[background] / [decorations] / [emphasis]

Then ask one question — three paths. Verbatim option copy: references/confirmation.md.

Path A — Quick confirm (trust auto-recommendation): generate a single outline using the recommended strategy + style → save to outline.md → Step 3.

Path B — Customize: ask five questions (strategy/style, layout, palette, count, optional notes) with the recommendation pre-filled — blanks keep the recommendation. Generate one outline with the user's choices → outline.md → Step 3. See references/confirmation.md.

Path C — Detailed mode: two sub-confirmations.

  • *Step 2a — Content understanding*: ask selling points (multi-select), audience, style preference (authentic / professional / aesthetic / auto), optional context. Update analysis.md.
  • *Step 2b — Three outline variants*: generate outline-strategy-a.md, outline-strategy-b.md, outline-strategy-c.md. Each MUST have a different structure AND a different recommended style — include style_reason in the frontmatter. Page-count heuristic: A ~4-6, B ~3-5, C ~3-4. Template: references/workflows/outline-template.md; frontmatter example in references/confirmation.md.
  • *Step 2c — Selection*: ask three questions (outline A/B/C/Combined, style, visual elements). Save selected/merged outline to outline.md → Step 3.

Step 3: Generate Images

With confirmed outline + style + layout + palette:

Visual consistency — image-1 anchor chain: character / mascot / color rendering drifts between calls unless you anchor them. Generate image 1 (cover) first WITHOUT --ref, then pass image 1 as --ref to every subsequent image. This is the single most important consistency trick for this skill — don't skip it even if the backend also supports a session ID.

For each image (cover, content, ending):

  1. Write the full prompt to prompts/NN-{type}-{slug}.md in the user's preferred language (backup rule applies).
  2. Generate:

- Image 1: no --ref (establishes the anchor). - Images 2+: add --ref <path-to-image-01.png>. - Backup rule applies to the PNG files.

  1. Report progress after each image.

Watermark (if enabled in EXTEND.md): append to the generation prompt:

Include a subtle watermark "[content]" positioned at [position].
The watermark should be legible but not distracting.

See references/config/watermark-guide.md.

Backend selection: per the Image Generation Tools rule at the top — use whatever is available, ask once if multiple, before any generation. Under --yes, use the EXTEND.md preference and fall back to the first available backend. Prompt files MUST exist before invoking any backend.

Session ID (if the backend supports --sessionId): use cards-{topic-slug}-{timestamp} for every image; combined with the ref chain this gives maximum consistency.

Step 4: Completion Report

Image Card Series Complete!

Topic: [topic]
Mode: [Quick / Custom / Detailed]
Strategy: [A/B/C/Combined]
Style: [name]
Palette: [name or "default"]
Layout: [name or "varies"]
Location: [directory]
Images: N total

✓ analysis.md
✓ outline.md
✓ outline-strategy-a/b/c.md (detailed mode only)

- 01-cover-[slug].png ✓ Cover (sparse)
- 02-content-[slug].png ✓ Content (balanced)
- ...
- NN-ending-[slug].png ✓ Ending (sparse)

Content Breakdown Principles

PositionPurposeTypical layout
Cover (image 1)Hook + visual impactsparse
Content (middle)Core value per imagebalanced / dense / list / comparison / flow
Ending (last)CTA / summarysparse or balanced

For the style × layout compatibility matrix, see the Style × Layout Matrix above.

Image Modification

ActionHow
EditUpdate prompts/NN-{type}-{slug}.md first, then regenerate with the same session ID
AddSpecify position, create prompt, generate, renumber subsequent files NN+1, update outline
DeleteRemove files, renumber subsequent NN-1, update outline

Always update the prompt file before regenerating — it's the source of truth and makes changes reproducible.

References

FileContent
references/confirmation.mdVerbatim AskUserQuestion copy for every confirmation path
references/style-presets.mdFull preset shortcut definitions
references/presets/<style>.mdPer-style element definitions
references/palettes/<name>.mdPer-palette color definitions
references/elements/canvas.mdAspect ratios, safe zones, grid layouts
references/elements/image-effects.mdCutout, stroke, filters
references/elements/typography.mdDecorated text, tags, text direction
references/elements/decorations.mdEmphasis marks, backgrounds, doodles, frames
references/workflows/analysis-framework.mdContent analysis framework
references/workflows/outline-template.mdOutline template with layout guide
references/workflows/prompt-assembly.mdPrompt assembly guide
references/config/preferences-schema.mdEXTEND.md schema
references/config/first-time-setup.mdFirst-time setup flow
references/config/watermark-guide.mdWatermark configuration

Notes

  • Auto-retry once on generation failure before reporting an error.
  • For sensitive public figures, use stylized cartoon alternatives.
  • Smart Confirm (Step 2) is required; Detailed mode adds a second confirmation (2a + 2c).

Changing Preferences

EXTEND.md lives at the first matching path listed in Step 0. Three ways to change it:

  • Edit directly — open EXTEND.md and change fields. Full schema: references/config/preferences-schema.md.
  • Reconfigure interactively — delete EXTEND.md (or ask "reconfigure baoyu-image-cards preferences" / "重新配置"). The next run re-triggers first-time setup.
  • Common one-line edits:

- preferred_image_backend: auto — default; runtime-native tool wins, falls back to the only installed backend, asks only if multiple non-native are present. - preferred_image_backend: codex-imagegen — pin to Codex's built-in. - preferred_image_backend: baoyu-imagine — pin to the baoyu-imagine skill. - preferred_image_backend: ask — confirm backend every run. - preferred_style: notion, preferred_layout: dense, preferred_palette: macaron, language: zh. - watermark.enabled: true + watermark.content: "@handle" — add a watermark.

平台分布

Codex

35.8%
按下载量换算7,887

Claude

29.87%
按下载量换算6,581

Cursor

19.33%
按下载量换算4,259

Gemini CLI

9.51%
按下载量换算2,095

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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