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Agent Skill · 图像处理

log-polish-enus-images(log Polish enus 图片)

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。

log-polish-enus-images 是图像处理类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;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 747。

总安装 2,940周安装 125GitHub Stars 公开资料未说明下载 1,030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:log-polish-enus-images(log Polish enus 图片)
来源仓库:https://github.com/j3ffyang/log-polish-enus-images
安装命令:
openclaw skills install log-polish-enus-images
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 log-polish-enus-images

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。

将技术博客草稿打磨为英文长文并生成配套英雄图像与章节配图。适合图像处理与视觉素材生成,保持技术术语与代码完整性。可用于内容创作、技术传播或多媒体文章生产。涉及人物或品牌图像时应核对授权与真实性。log-polish-enus-images 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 log-polish-enus-images;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

    它需要执行命令,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

log-polish-enus-images 怎么安装?

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

log-polish-enus-images 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。

log-polish-enus-images 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install log-polish-enus-images 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

log-polish-enus-images 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。

log-polish-enus-images 用的人多吗?

公开数据是累计安装 2,940 次,近一周安装 125 次,下载 1,030 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。

log-polish-enus-images 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

  • 需要执行命令,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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
log-polish-enus-images

log Polish enus 图片 · 本页

2,940—执行命令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
blog-polish-eng-images
description
Polish a technical blog draft into an 1000–1200 word, 4-5 section en-US article, preserve technical terms/code, and generate consistent hero + per-section image prompts when the user asks to polish and translate a blog with images.
author
Jeff Yang
version
1.0.0
tags
[openclaw, clawhub, blog, polish, translate, markdown, images, prompts]
triggers
["polish blog", "technical blog images", "blog draft images"]
metadata
openclaw
requires
[]
platforms
["linux", "darwin"]
env
[]
inputSchema
type
object
properties
draftPath
type
string
description
Path to the draft markdown. Defaults to ~/.openclaw/workspace/contentDraft/latestDraft.md
outputDir
type
string
description
Directory to save outputs. Defaults to ~/.openclaw/workspace/contentPolished/
subject
type
string
description
Short subject slug used in output filename (e.g. openclaw-skills). If omitted, infer from the draft title.
style
type
string
description
Visual style phrase reused for ALL images (e.g. "clean flat vector illustration, minimal isometric").
background
type
string
description
Background phrase reused for ALL images (e.g. "white background with subtle grid").
aspectRatioHero
type
string
description
Aspect ratio for hero image (e.g. "16:9 horizontal").
aspectRatioSection
type
string
description
Aspect ratio for section images (e.g. "4:3").
required
[]
outputSchema
type
object
properties
polishedPath
type
string
description
Path to the final polished markdown file.
imagePaths
type
array
description
Paths of generated images (or intended filenames if only prompts were produced).
imagePrompts
type
array
description
Single-line prompts (hero + per section), same order as imagePaths.
workflow
description
Resolve defaults and create timestamp
run
|
description
Read the draft content
run
|
description
Extract title, count words, identify section candidates
run
|
description
Generate polished content following Steps 2-5
run
|
description
Create hero + N prompts matching actual section headings
run
|
description
Emit final structured output for OpenClaw collector
run
|

Blog Polish (en-US) + Image Pack

This skill takes a technical blog draft and turns it into a publish-ready package:

  • Polish: spelling/grammar fixes + clarity improvements
  • Structure: reorganize into 3–4 sections total (not more)
  • Length: final content 1000–1200 words
  • Images: generate a hero prompt + one prompt per section, all in the same style/tone
  • Save: write everything to ~/.openclaw/workspace/contentPolished/ using yymmddhhmm-* naming

When to Use This Skill

When the user asks to polish a technical blog, and create images, you MUST use this skill and follow the workflow below step by step.

Use this when:

  • You already have a draft at ~/.openclaw/workspace/contentDraft/latestDraft.md
  • You want a polished en-US version without losing technical accuracy
  • You want consistent illustrations for the article

Defaults

If not provided via input:

  • draftPath: ~/.openclaw/workspace/contentDraft/latestDraft.md
  • outputDir: ~/.openclaw/workspace/contentPolished/
  • style: clean flat vector illustration, minimal isometric, software-engineering diagram vibe
  • background: white background with subtle grid
  • aspectRatioHero: 16:9 horizontal
  • aspectRatioSection: 16:9 horizontal

Workflow Step-by-Step

Step 0 — Resolve Paths and Timestamp

  1. Resolve defaults:

- draftPath = input.draftPath || "~/.openclaw/workspace/contentDraft/latestDraft.md" - outputDir = input.outputDir || "~/.openclaw/workspace/contentPolished/"

  1. Create a timestamp prefix ts in yymmddhhmm format (Linux/macOS):
date +"%y%m%d%H%M"
  1. Ensure output dir exists (shell is fine):
mkdir -p "~/.openclaw/workspace/contentPolished/"

Step 1 — Read Draft Exactly

Read the draft content in full before editing anything:

read_file --path {{draftPath}}

Step 2 — Extract Title, Topic, and Section Candidates

  1. Identify:

- Draft title (first # heading; otherwise infer a short title) - Main topic and intended audience

  1. Plan a 3–4 section outline (including intro/conclusion counts as sections if they have headings):

- Prefer: short intro, 2–3 core sections, short wrap-up - If the draft is long, merge similar paragraphs - If the draft is messy, reorder paragraphs for a cleaner flow

Step 3 — Polish English (Meaning First)

Before translating, make sure the English content makes sense:

  • Fix misspellings, grammar, punctuation
  • Paraphrase confusing sentences
  • Add missing connective tissue *only* where the meaning is unclear
  • Do not reduce content (no big deletions)

Step 4 — Enforce Length (1000–1200 Words) Without Cutting Meaning

Target final length 1000–1200 words (counting English words approximately by rough equivalence).

To fit without “reducing content”:

  • Tighten redundancy (same idea repeated)
  • Use shorter sentences
  • Prefer combining adjacent sentences that restate the same point

Step 5 — Add Citations If You Introduce Outside Facts

If you add any information that is not clearly present in the draft:

  • Add a short citation marker in text like: [^1]
  • Add a footnotes section at the end:
## References
[^1]: Source title — URL

Step 6 — Generate Image Prompts (Hero + Per Section)

Create one single-line prompt for:

  • Hero image (for the whole post)
  • Each section (exactly one per section heading)

Use this strict ordering and keep the same style/tone across all prompts:

[Section role] of [topic]: [subject] doing [action], in [style], [angle/composition], [lighting/color], [level of detail], [background], [aspect ratio]

Constraints:

  • No text in the image (prefer icons/arrows)
  • Keep a consistent palette (neutral + one accent color)
  • Keep prompts to a single line each

Step 7 — Save Outputs

  1. Decide subject:

- subject = input.subject || slugify(title) (lowercase, hyphens)

  1. Write the polished markdown:

- {{outputDir}}/{{ts}}-{{subject}}.md

  1. Determine image filenames:

- Hero: {{ts}}-main.png - Per section: {{ts}}-section1.png, {{ts}}-section2.png, ...

  1. Save:

- Write the polished .md file via write_file - For images: - If you have an image-generation tool available in your OpenClaw setup, generate and save the actual PNG/JPGs - Otherwise: still create an image-prompts block inside the markdown and return the intended filenames (so you can generate them later)

Output Format (What You Return)

Return:

  • polishedPath
  • imagePaths (actual or intended)
  • imagePrompts (single-line prompts in the same order)

Also print a short summary:

## Summary
- Sections: N
- Length: ~X words
- Images: 1 hero + N section prompts

Example Invocation

User says:

  • “Polish my latest draftand make images.”

You do:

  • Read from ~/.openclaw/workspace/contentDraft/latestDraft.md
  • Produce ~/.openclaw/workspace/contentPolished/2603121010-openclaw-skills.md
  • Produce 2603121010-main.png + 2603121010-section1.png ...

Dependencies

None (pure Markdown in/out). Uses the same file read/write capability as your other skills.

平台分布

OpenClaw

86.22%
按下载量换算888

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install log-polish-enus-images 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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