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Agent Skill · 图像处理

token-image(令牌图像)

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。

token-image 是图像处理类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,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 836。

总安装 2,564周安装 109GitHub Stars 1下载 898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:token-image(令牌图像)
来源仓库:https://github.com/czl9707/token-image
安装命令:
openclaw skills install token-image
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 token-image

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。

使用设计令牌生成主题社交或营销图像组件。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。适合创建 React 组件并渲染为 PNG 文件。当用户要求生成图像时自动触发使用。token-image 属于图像处理类 Skill,可作为该场景下的辅助能力补充。安装前需确认是否会生成图片或访问外部服务。

建议核对版权和授权边界后再用于公开展示。

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 token-image;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

    它需要操作浏览器,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

token-image 怎么安装?

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

token-image 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。

token-image 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

token-image 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。

token-image 用的人多吗?

公开数据是累计安装 2,564 次,近一周安装 109 次,下载 898 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。

token-image 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

  • 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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
token-image

令牌图像 · 本页

2,5641操作浏览器MIT-0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

name
token-image
description
>

token-image

Generate a series of social/marketing image React components in the same theme.

Vocabulary

TermWhat it isScope
ViewportShared outer frame component. Safe-area padding, content alignment, root container, optional branding. Written once, reused by every image in the set.Per set
StylesheetShared CSS file. Starts from default-styles.css, adds preset-specific overrides. Styles all typography, cards, grids, and layout via token CSS vars. Written once, imported by every image.Per set
BriefPer-image content instructions written by the orchestrator. Includes exact text strings, layout description, creative direction, metadata. Writers implement the brief — they do not make content decisions.Per image
LayoutContent arrangement description inside the Viewport. Written by the orchestrator per image (e.g., "split — title left, 2x2 cards right"). The shared agent creates CSS classes to support all layouts in the set.Per image

Supporting Files

FilePurposeWhen to use
scripts/init.shBootstrap workspace (tokens, deps, --preset <name> or --tokens <path> required)After intake: if .token-image/ workspace missing
assets/<preset>/tokens.jsonToken set for the chosen design systemSelected during intake; copied to .token-image/tokens/ by init.sh
assets/<preset>/design-guide.mdDesign principles and stylesheet overrides for the chosen token setRead during intake after preset selection; injected into agent prompts
.token-image/src/token.active.jsonProject's active token fileRead in full during intake; passed to every agent
references/default-styles.cssBase stylesheet with typography, card, grid, and layout stylesRead by shared-files agent in Phase 2 Step 2
references/viewports.mdViewport examples (2-3 variants)Read by shared-files agent in Phase 2 Step 2
references/components.mdComponent snippets (Card, Grid, decoration patterns)Read by Writer agents in Phase 2 Step 3
prompts/shared.mdShared files agent prompt (Viewport + Stylesheet)Read by agent in Phase 2 Step 2
prompts/writer.mdWriter agent promptRead by Writer agents in Phase 2 Step 3
prompts/reviewer.mdReviewer agent promptRead by Reviewer agents in Phase 2 Step 3

Phase 0: Pre-flight

Announce: "I'm using the token-image skill."

Check for .token-image/ workspace directory in the project root.

  • If present: note that workspace exists. Read .token-image/src/token.active.json for reference.
  • If missing: note that workspace needs initialization. Do NOT run init.sh yet — wait until Phase 1 when the user picks a preset.

Ensure Playwright browsers are installed:

npx playwright install chromium

This is idempotent — if already installed, it's a no-op.


Phase 1: Intake

Before generating anything, ask the user these questions. Skip any that were already answered in the initial prompt.

  1. Theme — Which token set should I use?

- Available presets: {list all subdirectories in <skill_base_dir>/assets/} - Or paste a path to your own tokens.json (with optional design-guide.md alongside it). This will be passed as --tokens <path> to init.sh.

  1. Images — What should each image be about, and how many?

(e.g. "4 banners: Hooks, Context, Suspense, Server Components")

  1. Format — Which image format?

- twitter-card 1200×600 - instagram-square 1080×1080 - og-image 1200×630 - custom — User specify width and height

  1. Layout — Describe the layout for each image.

What goes where? (e.g., "title top-left, 2x2 card grid on right", "full-canvas hero with oversized title", "numbered steps down the left side") You can describe one layout for all images or a different one per image. If you're not sure, say "auto" and I'll pick based on content.

  1. Branding — What should be consistent across all images?

(e.g., "logo bottom-right", "series label 'REACT SERIES · PART N' in footer", "no branding", "subtle watermark center-bottom") This becomes part of the shared Viewport that wraps every image. If none, say "none" and I'll keep the viewport clean.

Wait for the user's answers before proceeding. If the user says "auto" or leaves something blank, make a reasonable choice and state it.

After the user selects a preset or provides a custom token file:

  • If workspace is missing, run init.sh:
  # For a built-in preset:
  bash <skill_base_dir>/scripts/init.sh --preset <chosen_preset>
  # For a custom token file:
  bash <skill_base_dir>/scripts/init.sh --tokens <path/to/tokens.json>
  • If workspace exists but uses a different preset, copy the chosen preset's tokens to active:
  cp .token-image/tokens/<chosen_preset>/tokens.json .token-image/src/token.active.json
  • For a built-in preset: read <skill_base_dir>/assets/<preset>/tokens.json into context as {token_json} and <skill_base_dir>/assets/<preset>/design-guide.md into context as {design_guide}
  • For a custom token file: read the custom tokens.json and optionally design-guide.md if it exists alongside it

Once you have all answers, confirm the plan:

Got it. Here's what I'll generate:
- Format: {format} ({width}×{height})
- Theme: {token_file}
- Branding: {user's branding spec from Q5}
- Images:
  1. {title 1} — {subtitle 1}
    - Layout: {layout description 1}
  2. {title 2} — {subtitle 2}
    - Layout: {layout description 2}
  ...

I'll plan content, create shared Viewport + Stylesheet, then one component per image.
Proceed?

Only proceed after the user confirms.


Phase 2: Generate

Step 1: Content Planning

Do NOT delegate this step. The orchestrator (you) writes a content brief for every image in the set.

Based on the user's intake answers, produce two things:

A. Shared element inventory — decide what's shared across the whole set, informed by the user's branding answer (Q5):

  • Viewport variant needed (hero for one image, standard for the rest)
  • Branding and metadata placement from user's Q5 answer (logo position, series label, watermark, etc.)
  • Any special alignment or spacing requirements
  • Write this as a short list the shared-files agent will use.

B. Per-image brief — for each image, describe what goes inside the Viewport. Include:

  • Exact text strings (title, subtitle, body, metadata)
  • Layout description (what goes where)
  • Creative direction — a specific aesthetic target for this image (position, scale, density, tension). This is what makes images feel distinct rather than generic.

Example output for a 4-image set:

SHARED:
- Viewport: hero variant (Image 1), standard variant centered (Images 2-4)
- Stylesheet: Nothing preset, no overrides needed
- Metadata format: "REACT SERIES · PART N" for all images, bottom
- No branding

  Image 1 — hero, full canvas:
    Layout: hero — oversized display title pushed to bottom-right, tagline below
    Creative direction: "Poster-style, 70% whitespace above, oversized display text, bottom-right anchored"

  Image 2 — split, text left + decoration right:
    Layout: split — title and body left panel, dot-grid background pattern right panel
    Title: "useState". Subtitle: "Managing local component state".
    Body: short paragraph about useState and when to reach for it.

  Image 3 — split, swapped:
    Layout: split — dot-grid background pattern left panel, title and body right panel
    Title: "useEffect". Subtitle: "Handling side effects in function components".

  Image 4 — title above grid:
    Layout: title spanning full width, 2×2 card grid below
    Title: "Hook Patterns". Cards:
    - STATE: "Manage local state with useState"
    - EFFECT: "Handle side effects with useEffect"
    - CONTEXT: "Share data across the component tree"
    - CUSTOM: "Build reusable logic abstractions"

Consistency rules (enforced by the orchestrator when writing briefs):

  • Title style: All titles in the set should have the same character — same approximate length, same tone. Don't mix single-word titles with long phrases.
  • Layout variety: Avoid repeating the same layout for every image. Aim for at least 2 different layout patterns in a set of 3+ images.
  • Layout descriptions: Be specific about what goes where. "Split with cards" is better than "split". "Title above, 2x2 grid below" is better than "grid".
  • Content density: If content for an image is too dense, flag it and suggest adding another image to the set.
  • No empty panels: If a split layout would leave one side mostly empty, consider a different layout or move content to fill it.
  • No random decoration: Do not instruct Writers to add standalone decorative elements (dots, shapes, circles) unless the creative direction explicitly calls for them. Background patterns are acceptable.

Step 2: Generate shared files (Viewport + Stylesheet)

Dispatch one agent to create the Viewport component and the complete stylesheet. This agent is the layout architect — it reads the full content plan and creates CSS classes for every layout the images need.

Tell the agent:

  • The format dimensions (width, height, name) and the full content plan (from Step 1, including layout descriptions for every image)
  • To read <skill_base_dir>/prompts/shared.md for full instructions
  • To read .token-image/src/token.active.json for tokens
  • To read <skill_base_dir>/references/viewports.md for viewport examples
  • To read <skill_base_dir>/references/default-styles.css for the base stylesheet
  • To read <skill_base_dir>/references/components.md for layout pattern reference (CSS + TSX pairs)
  • To read <skill_base_dir>/assets/<preset>/design-guide.md for the design guide
  • The preset name

The agent writes directly to .token-image/src/viewport.tsx and .token-image/src/styles.css.

The stylesheet must include an "available classes" comment block listing all layout CSS classes, so writers know what's available.

Do NOT run the Reviewer on shared files — they are structural, not design-heavy.

Step 3: Dispatch per-image agents

This step runs in rounds. Each round: all Writers in parallel → batch render → all Reviewers in parallel. Max 3 rounds per image.

Round N:

  1. Dispatch Writer agents for all images in parallel using the Agent tool.

Tell each Writer agent: - The content brief for this specific image (from Step 1), the format spec (width, height, name), the layout description (from the brief's Layout: field), the creative direction, and the file index - To read <skill_base_dir>/prompts/writer.md for full instructions - To read .token-image/src/token.active.json for tokens - To read .token-image/src/viewport.tsx for the Viewport component - To read .token-image/src/styles.css for available CSS classes (the "available classes" comment block at the top lists all layout classes) - To read <skill_base_dir>/references/components.md for component patterns - To read <skill_base_dir>/assets/<preset>/design-guide.md for the design guide - The preset name

The Writer writes the component directly to .token-image/src/<format>-<index>.tsx.

  1. Batch render all components. After all Writers complete, run:
   cd .token-image && npm run render

This renders every .tsx → .png in one pass (single Playwright session). The PNGs are saved to .token-image/src/<format>-<index>.png.

  1. Dispatch Reviewer agents for all images in parallel using the Agent tool.

Tell each Reviewer agent: - The content brief for this image - To read <skill_base_dir>/prompts/reviewer.md for full instructions - To read .token-image/src/viewport.tsx for the Viewport component - To read .token-image/src/styles.css for the shared stylesheet - To read .token-image/src/token.active.json for tokens - To read .token-image/src/<format>-<index>.tsx for the component to review - To read .token-image/src/<format>-<index>.png for the rendered image (already rendered by the orchestrator — reviewer does NOT run render) - The Reviewer uses multi-modal capabilities to check both code compliance AND visual quality

  1. Collect results. For any image that didn't PASS, carry it into the next round (updated Writer + re-render that component + Reviewer again). Images that PASS are done.

For re-renders of individual components in subsequent rounds:

   cd .token-image && npm run render -- <format>-<index>

Run max 3 rounds total. After 3 rounds, accept whatever state the remaining images are in.


Phase 3: Output

Save files to .token-image/src/:

FilePurpose
viewport.tsxShared Viewport component
styles.cssShared stylesheet (default + preset overrides)
<format>-<index>.tsxPer-image components

Create the .token-image/src/ directory if it doesn't exist.

After all images are written and reviewed, summarize:

  • How many components were generated
  • Any images that hit the 3-round limit with remaining issues (and what they are)
  • All PNGs have been rendered to .token-image/src/
  • Reminder: run cd .token-image && npm run render [component] to re-render if needed

Then automatically launch the visual editor:

cd .token-image && npm run editor

This opens the editor in the user's browser so they can visually inspect and tweak tokens immediately.


Phase 4: Next Steps

After generating all components, tell the user:

"Done. The visual editor should be open in your browser. Useful commands: npm run render # re-render all .tsx → .png npm run render -- square-1 # render one by name npm run render:2x -- square-1 # render one at 2x dimensions npm run editor # re-launch visual token editor (if closed)"

IMPORTANT

  • Never skip the Reviewer step
  • Never output partial results — wait for all parallel agents to complete
  • Always plan content first (Step 1), then generate shared files (Step 2), then dispatch Writers (Step 3)
  • Content decisions belong to the orchestrator — Writers implement, not interpret
  • Creative direction is mandatory in every brief — this is what prevents generic output

平台分布

OpenClaw

95%
按下载量换算853

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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