OpenMAIC is a multi-agent classroom platform that uses agents to plan, build, and revise interactive courses from prompts and uploaded materials. It is designed for immersive learning experiences and supports course components such as slides, quizzes, interactives, projects, images, video, voices, and PowerPoint imports, with catalogue skills covering its workflows.
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 THU-MAIC/OpenMAIC --skill social-emotional-learninggit clone --depth 1 https://github.com/THU-MAIC/OpenMAICWrote 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/thu-maic/openmaic/social-emotional-learning)<a href="https://agentmods.dev/skills/thu-maic/openmaic/social-emotional-learning"><img src="https://agentmods.dev/badge/skills/thu-maic/openmaic/social-emotional-learning/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/thu-maic/openmaic/social-emotional-learning"><img src="https://agentmods.dev/badge/skills/thu-maic/openmaic/social-emotional-learning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00084 | $0.00968 |
| Opus 5 | $0.00042 | $0.00484 |
| Sonnet 5 | $0.00017 | $0.00194 |
| Haiku 4.5 | $0.00008 | $0.00097 |
Grade A, and why
social-emotional-learning 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 11d 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.
What it actually says
社会情感学习（SEL）
把社会情感学习作为平行目标嵌入概念主课：不替换用户真正关心的学科概念，而是改变学生如何经历它。
stage-design 仍然约束课堂的创建和持久化流程。如果同时使用 /understanding-by-design，先确定大概念、基本问题与表现性任务，再在页面计划中嵌入 SEL。每一个 SEL 设计都要能回答“它在服务哪个概念理解”；答不出就删除。
先声明平行目标
在页面计划前，用一句话分别声明：
- 概念目标：学生要理解或迁移什么；
- SEL 平行目标：学生要在这段学习中练习哪种能力，以及什么行为能证明它发生了。
优先从下列能力中选择与概念任务最贴合的 1–2 项，不要一节课堂包办全部：
- 自我认识与自我管理：学生能觉察困惑、挫败、好奇或走神，并做出一步调节。
- 社会意识与同理：从他人或利益相关者的立场重看同一内容。
- 人际关系与协作：讲清推理，接受并回应建设性批评，对观点而不是对人反驳。
- 负责任决策：评估不同解释或行为的后果，并为选择提供理由。
四个 SEL 嵌入点
不必为 SEL 另加四页；把目标嵌入原有页面的 brief 与交互中：
- 开场 Hook：在开场
slide中加一个情绪或觉察拍，让学生叫出“今天我可能会卡在哪里”的感受。 - 概念建立：在
slide中设计一段有实质分歧的多智能体讨论，练习换位与协作；分歧落在观点上，不落在人上。 - 亲手做：让
interactive存在可预期的受挫、反馈与重试路径，用来练习自我管理和韧性；失败不能是死路。 - 收束反思：同时追问“你理解了哪个概念”与“你练到了哪种社会情感能力”，让学生将两种收获分别说清。
多智能体的作用
- 老师：引导学生说出感受、换位思考、承认合理分歧，并及时把讨论带回概念主线。
- 学生代理：提出不同理解、真实质疑或“我卡住了”的状态，邀请学习者参与、判断或帮助修正。
不用代理宣读 SEL 术语。让能力通过可观察的对话、选择、反馈和重试发生。
质量与安全关口
- SEL 目标与概念目标分开声明，不混成空泛的“综合素养”。
- 每个嵌入点都标明它服务的概念与可观察的 SEL 能力。
- 情绪表达被接纳且不被评判；不要强迫学生公开个人创伤、心理状况或隐私经历。
- 不进行心理诊断，不把学习挫折病理化，不以羞辱、公开排名或同伴压力驱动参与。
interactive必须有受挫—反馈—重试路径；收束页同时呈现概念收获与能力收获。
边界
本 Skill 用于把 SEL 嵌入学科概念课，不用于以 SEL 本身为内容主线的独立心理课、班会课或情绪课。如果用户想让 SEL 成为与学科概念并列的第二条完整主线，先用 ask_user 确认范围。
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.
- 11d ago First seen · 54 lines · 84 tokens per session scan A 4aea1736a885
social-emotional-learning is a skill published in the GitHub repository THU-MAIC/OpenMAIC (34,951 stars, last pushed 2d ago), licensed MIT. It adds 84 tokens to every session and 968 once invoked, about $0.0004 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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