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 skills add ufy2024/AuC --skill intelligent-content-systemgit 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/intelligent-content-system)<a href="https://agentmods.dev/skills/ufy2024/auc/intelligent-content-system"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/intelligent-content-system/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.
<a href="https://agentmods.dev/skills/ufy2024/auc/intelligent-content-system"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/intelligent-content-system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 367 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Agent Snooping · line 37 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 331 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00153 | $0.04832 |
| Opus 5 | $0.00077 | $0.02416 |
| Sonnet 5 | $0.00031 | $0.00966 |
| Haiku 4.5 | $0.00015 | $0.00483 |
Grade A, and why
intelligent-content-system 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 9d 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 — 592 lines — stays where its author put it; the contents beside it link to each section on GitHub.
智能内容创作与发布系统
任务目标
- 本技能用于：从内容获取到多平台发布的智能化全流程
- 能力包含：
- 自动识别用户需求场景
- 智能编排技能调用链
- 网页内容采集与转换
- 文章智能配图
- 小红书图文生成
- 热点内容创作
- 多平台自动发布
- 触发条件：用户提出内容创作或发布相关需求
核心特性
1. 智能场景识别
系统会自动分析用户输入，识别以下场景：
| 场景代码 | 场景名称 | 触发关键词 | 技能链 |
|---|---|---|---|
| A1 | 采集并发布 | "采集+发布"、"抓取+推送" | url-to-markdown → format → illustrator → publish |
| A2 | 采集并配图 | "采集+配图"、"抓取+插图" | url-to-markdown → illustrator |
| A3 | 采集转小红书 | "采集+小红书"、"网页转小红书" | url-to-markdown → xhs-images |
| B1 | 热点文章生成 | "热点+文章"、"爆款+公众号" | wechat-hotspot-publisher |
| B2 | 热点图文生成 | "热点+小红书"、"爆款+图文" | wechat-hotspot → xhs-images |
| B3 | 热点多平台发布 | "热点+多平台" | wechat-hotspot → multi-publish |
| C1 | 文章配图 | "配图"、"插图"、"加图" | article-illustrator |
| C2 | 转小红书图文 | "转小红书"、"生成图文" | xhs-images |
| C3 | 多平台发布 | "发布到"、"推送到" | format → publish |
| D1 | 仅采集网页 | "采集"、"抓取"、"保存网页" | url-to-markdown |
| D2 | 仅配图 | "配图"（单独） | article-illustrator |
| D3 | 仅小红书图文 | "小红书图文"（单独） | xhs-images |
| D4 | 仅发布 | "发布"（单独） | publish |
详细识别规则见：references/scenario-detection.md
2. 自动参数收集
系统会根据场景自动收集必需参数：
- URL：网页地址（用于采集场景）
- 关键词：热点话题关键词（用于热点场景）
- 文件路径：Markdown文件路径（用于优化场景）
- 平台列表：目标发布平台（微信/小红书/X/B站）
- 风格偏好：小红书图文风格（可选）
- 是否需要登录：网页是否需要登录（可选）
3. 进度实时反馈
执行过程中会实时反馈进度：
✓ 场景识别：A1 - 采集并发布
✓ 参数收集完成
→ 步骤1/4：采集网页内容...
✓ 步骤1/4：内容已采集（3500字）
→ 步骤2/4：格式优化...
✓ 步骤2/4：格式已优化
→ 步骤3/4：生成配图...
✓ 步骤3/4：已生成3张配图
→ 步骤4/4：发布到微信公众号...
✓ 步骤4/4：已推送到草稿箱
✅ 任务完成！
操作步骤
标准流程
-
用户描述需求
- 用户用自然语言描述需要完成的任务
- 示例："采集这篇文章并发布到微信公众号"
-
场景识别
- 系统分析用户输入，识别场景代码
- 确定需要调用的技能链
- 参考：references/scenario-detection.md
-
参数收集
- 系统提取用户输入中的参数（URL、关键词等）
- 如有缺失，询问用户补充
- 确认所有必需参数已收集
-
工作流执行
- 按照技能链顺序执行各个步骤
- 每步完成后反馈进度
- 将上一步输出作为下一步输入
- 参考：references/workflow-templates.md
-
结果汇总
- 展示最终结果
- 提供文件路径或发布链接
- 询问是否需要调整
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.
- 9d ago First seen · 592 lines · 153 tokens per session scan A b049378dc48c
intelligent-content-system is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 153 tokens to every session and 4,832 once invoked, about $0.0008 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 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
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…
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.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…