AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.
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.
npx agentmods add skills/ufy2024/auc/article-illustrator-article-illustratornpx skills add ufy2024/AuC --skill article-illustrator-article-illustratorgit clone --depth 1 https://github.com/ufy2024/AuCWrote 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.
[](https://agentmods.dev/skills/ufy2024/auc/article-illustrator-article-illustrator)<a href="https://agentmods.dev/skills/ufy2024/auc/article-illustrator-article-illustrator"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/article-illustrator-article-illustrator.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00067 | $0.01527 |
| Opus 5 | $0.00034 | $0.00763 |
| Sonnet 5 | $0.00013 | $0.00305 |
| Haiku 4.5 | $0.00007 | $0.00153 |
Grade A, and why
article-illustrator 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 6d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
文章智能配图
分析文章结构与内容，识别需要视觉辅助的位置，生成风格灵活的配图。
任务目标
- 分析文章结构和内容，逐段识别需要配图的位置
- 为每个配图位置生成详细的配图计划和提示词
- 使用图像生成能力创建符合风格规范的插画
- 将图片插入到文章对应位置
触发条件
用户明确要求：
- "给文章配图"
- "为文章生成插图"
- "添加配图"
- "为这篇文章生成一些图片"
工作流程
步骤一：获取文章内容
根据用户提供的信息获取文章：
- 本地路径：读取指定 Markdown 文件
- URL：自动下载 Markdown 内容到临时位置
步骤二：分析配图需求
逐段分析文章，识别需要配图的位置。
配图的三种作用：
- 信息补充：帮助理解抽象概念（如"小步迭代"用滑板→自行车→汽车演进图）
- 概念具象化：将抽象观点转化为具体画面，让读者一眼就懂
- 引导想象：营造氛围、激发联想，增强阅读体验
适合配图的内容：
- 抽象概念需要视觉化
- 流程/步骤需要图示
- 对比关系需要可视化
- 核心观点需要强化
- 场景描述需要引导想象
- 情绪/氛围需要烘托
不需要配图的内容：
- 已经很直观的描述（如代码示例、具体数字）
- 简单的列表枚举
- 引用的原话
配图数量（按文章长度）：
- 每个主要章节至少考虑 1 张，优先选择核心观点和抽象概念
- 开头/结尾可酌情增加 1 张（如需要氛围烘托）
- 原则：宁多勿少，视觉内容能显著提升阅读体验
步骤三：生成配图计划
为每个配图位置创建结构化计划：
**配图 1**
**插入位置**：[章节名称] / [段落描述]
**配图目的**：[为什么这里需要配图]
**视觉内容**：[图片应该展示什么]
**文件名**：illustration-[slug].png
文件命名规则：
- 格式：
illustration-[slug].png - slug 使用有意义的英文描述，符合规范（小写字母、数字、连字符）
- 示例：
illustration-product-evolution.png、illustration-ai-vs-human.png
步骤四：生成配图
根据配图计划，为每张图片生成详细的视觉描述并创建图片。
生成要求：
- 按顺序生成每张图片，输出进度："已生成 X/N 张"
- 根据内容选择合适的风格（参考
references/style-guide.md） - 每张图片包含：画面主体、布局、配色、文字（如有）
图片属性：
- 比例：16:9 横向
- 风格：根据内容选择极简扁平矢量、科幻未来感、手绘涂鸦风等
- 配色：遵循默认色彩方案或风格变体方案
步骤五：更新文章
将生成的图片插入到文章对应位置。
插入规则：
- 图片插入到对应段落之后
- 图片前后各留一个空行
- 使用 Markdown 语法：
 - alt 文本使用简洁的中文描述（5-10 字）
图片保存位置：
- 在文章所在目录创建
imgs/子目录 - 所有图片保存在该目录中
步骤六：输出汇总
完成所有配图后，输出汇总信息：
配图完成！
文章：[文章路径]
生成数量：X/N 张成功
配图位置：
- illustration-[slug].png → [章节/段落位置]
[如有失败]
失败项：
- illustration-[slug].png：[失败原因]
配图策略
识别关键位置：
- 文章开头：是否有需要氛围烘托的引言
- 每个章节：核心概念是否抽象
- 流程步骤：是否需要可视化
- 对比内容：是否需要图示
- 总结部分：是否需要强化记忆
优先级排序：
- 抽象概念（优先级最高）
- 核心观点
- 流程/步骤
- 对比关系
- 氛围烘托
风格选择原则：
- AI、前沿技术 → 科幻未来感
- 轻松、思考类 → 手绘涂鸦风
- 流程、对比、数据 → 信息图表风
- 叙事、想象类 → 场景插画风
- 其他 → 极简扁平矢量（默认）
资源索引
- 视觉风格规范：见 references/style-guide.md
- 术语对照表：见 references/terminology.md
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.
- 6d ago First seen · 177 lines · 67 tokens per session scan A e3886526d949
article-illustrator is a skill published in the GitHub repository ufy2024/AuC (1,091 stars, last pushed 1mo ago), licensed MIT. It adds 67 tokens to every session and 1,527 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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