image-render

image-render is a skill for Claude Code, Codex from yunshu0909/yunshu_skillshub. It costs 142 tokens per session (2,177 once invoked), scanned A, original, MIT.

An image-making workflow that turns an article into a coordinated set of illustrations using a chosen visual style.

In plain words
What is it for?
It is for planning article illustrations, trying several visual styles, producing a full matching set, and saving a preferred default style.
Why use it?
It separates planning what each picture should show from sending the final prompts to an image generator, reducing ambiguity about content and on-image text.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: runs codex exec; mentions Codex.

Good fit It is for planning article illustrations, trying several visual styles, producing a full matching set, and saving a preferred default style.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yunshu0909/yunshu_skillshub/image-render
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yunshu0909/yunshu_skillshub --skill image-render
Clone the repo
git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for image-render

README.md
[![agentmods](https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/image-render/github.svg)](https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/image-render)
Your own site
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/image-render"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/image-render/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for image-render

Your own site · 80×15
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/image-render"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/image-render.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 142 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,177 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00142 $0.02177
Opus 5.5 $0.00057 $0.00871
Sonnet 5.5 $0.00028 $0.00435
Haiku 4.5 $0.00014 $0.00218

Measured 13d ago against content hash 58845928599b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

image-render scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/_lib.py, scripts/add_sample.py, scripts/build_prompts.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

visualization/image-render/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

配图出图(image-render)

把文章变成一套风格统一的配图。Claude 负责想清楚画什么、图上写哪些字;Codex 只负责把提示词原样交给 imagegen 出图;脚本负责检查和核对。

下文 S 指本 skill 的脚本目录(本文件所在目录下的 scripts/):

S=<本 SKILL.md 所在目录>/scripts

第一次用

  1. python3 $S/doctor.py:环境自检(Codex 装没装、登没登录、Python)。有 ✗ 先按提示补。
  2. 没有默认风格时,开风格选择页让用户看图选(见下面「默认风格」)。

默认风格

风格 = 有样张的风格,用户看图选。选一次存成默认,之后每次直接用,不再每次问。

用户说 怎么做
(开工时) python3 $S/settings.py get style。打印出编号 → 告诉用户「本次用默认风格 X(编号 · 名字),要换说一声」,直接往下做。什么都没打印 = 还没设,走「第一次选」
第一次选 / 「换默认风格」 先把画面单给用户确认,再 python3 $S/style_picker.py <任务目录>/风格选择.html 并打开;用户报编号(或贴回 ♡ 复制的内容)就视为选定默认 → python3 $S/settings.py set style <编号>
「这次用 N42」 只这一次用,不改设置:adapt 文件名里写这个编号(如 1-N42.txt)。真正决定用哪张风格卡的是文件名里的编号;scenes.md 顶部写一行「本次风格:N42」只是备忘
「给我几个风格看看」 探索:选 3–4 种(reference/recommend.md 按内容类型推荐),用用户自己的同一张图各出一版对比;用户选中的可以设成新默认
「你推荐」 才参考 reference/recommend.md 和 reference/taste.md(作者口味)

设置存在 ~/.image-render/settings.json,升级 skill 不会被覆盖;家目录写不进时(Codex 沙盒)自动存到当前项目的 .image-render/,以后在这个项目里用会自动读到;也可以用环境变量 IMAGE_RENDER_HOME 指定。

流程

步 做什么 谁 详细
1 画面单 每张图:画幅 / 用途、讲什么、内容类型、必含文字(「」包住)。写完给用户确认(用户说「直接做」可跳过) Claude → 用户 stages/01-scenes.md
2 定风格 默认风格;没有就看图选;探索时选 3–4 种 用户 stages/02-pick-style.md
3 风格适配 核心:按风格卡的叙事语法为每张图重新设计场景、比喻、文字载体 Claude stages/03-adapt.md
4 出图 检查 → 拼提示词 → Codex 原样出图 → 核对提示词逐字。第一次用或刚换默认风格:先只出第 1 张给用户看,满意再出剩下的 脚本 + Codex stages/04-render.md
5 挑图与迭代 Claude 先逐张看图上的字;对比页给用户标 ♡;不满意一次只改一处;选中的图写回样张 Claude → 用户 stages/05-review.md

新增风格

用户想要库里没有的风格(给一句描述或一张参考图):

  1. 找到自建风格目录(python3 $S/settings.py show 第二行,一般是 ~/.image-render/styles/;第一次加风格时可能还不存在,先 mkdir -p),复制 templates/style-card.md 进去,命名为 U01-<风格名>.md(编号 U01、U02… 接着排,文件名 = 编号-名字),填好。风格块只写「长什么样」——材质、线条、配色、文字长相、不要什么,不写版式。
  2. 用用户手头的一张图按新卡出一张试图(adapt 文件名写 1-U01.txt)。
  3. 用户说喜欢 → python3 $S/add_sample.py U01 <试图路径>(要设成默认就加 --default)。这一条命令会缩略图片、放进样张目录、写进卡片。有样张才算进库,风格选择页才会显示它。
  4. 用户不喜欢:在风格块里只改一处再出一版;放弃就删掉这张卡,不留空卡。

Read the full file on GitHub · 92 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 92 lines · 142 tokens per session scan A 58845928599b

Subscribe to this mod's changes

image-render is a skill published in the GitHub repository yunshu0909/yunshu_skillshub (784 stars, last pushed 13d ago), licensed MIT. It adds 142 tokens to every session and 2,177 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-12.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

component-fixtures

Use when creating or updating component fixtures for screenshot testing or their shared infrastructure, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, validation, and common pitfalls.

microsoft/vscode · 53 tokens