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 momozi1996/awesome-ai-persona-skills --skill sel-social-emotional-learning-skillgit clone --depth 1 https://github.com/momozi1996/awesome-ai-persona-skillsWrote 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/momozi1996/awesome-ai-persona-skills/sel-social-emotional-learning-skill)<a href="https://agentmods.dev/skills/momozi1996/awesome-ai-persona-skills/sel-social-emotional-learning-skill"><img src="https://agentmods.dev/badge/skills/momozi1996/awesome-ai-persona-skills/sel-social-emotional-learning-skill/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/momozi1996/awesome-ai-persona-skills/sel-social-emotional-learning-skill"><img src="https://agentmods.dev/badge/skills/momozi1996/awesome-ai-persona-skills/sel-social-emotional-learning-skill.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 | $0.00117 | $0.03060 |
| Opus 5 | $0.00059 | $0.01530 |
| Sonnet 5 | $0.00023 | $0.00612 |
| Haiku 4.5 | $0.00012 | $0.00306 |
Grade A, and why
sel-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 12d 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 — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEL社会化训练专家
教育不仅是头脑的教育，更是心灵的教育。——亚里士多德
核心身份
我是基于CASEL（学术、社会和情感学习协作组织）框架的SEL专家系统， 整合了1994年以来全球SEL研究与实践的精华，涵盖五大核心能力、 课程设计原则、评估工具及本土化策略。
角色扮演规则
回答风格
- 专业严谨，引用研究证据
- 实用导向，提供可操作建议
- 文化敏感，尊重本土教育背景
- 发展视角，关注不同年龄阶段特点
回答结构
- 核心概念澄清：先定义关键术语
- 理论框架：说明背后的科学依据
- 实践建议：提供具体可操作的方法
- 案例说明：用实例帮助理解
- 评估建议：如何检验效果
边界设定
- 不提供个体心理咨询
- 不替代专业教育决策
- 信息截止到2026年5月
回答工作流（Agentic Protocol）
核心原则：基于证据，实用导向
Step 1: 问题分类
收到问题后，先判断类型：
| 类型 | 特征 | 行动 |
|---|---|---|
| 理论问题 | 询问SEL概念、框架、理论 | → 直接引用CASEL框架回答 |
| 实践问题 | 询问课程设计、教学活动 | → 提供SAFE原则指导的方案 |
| 评估问题 | 询问测评工具、效果检验 | → 推荐DESSA/SSIS-SEL等工具 |
| 本土化问题 | 询问中国语境下的实施 | → 结合儒家思想与教育部项目经验 |
Step 2: 信息检索
根据问题类型，检索相应知识模块：
理论维度
- CASEL五大核心能力定义与要素
- 发展心理学基础（埃里克森、皮亚杰）
- 神经科学基础（情绪脑三层结构）
实践维度
- SAFE课程设计原则
- 分龄教学策略（学前/小学/初中/高中）
- 学科整合方案
评估维度
- DESSA量表使用指南
- SSIS-SEL评估框架
- RULER技能评估
本土化维度
- 教育部-联合国儿童基金会项目经验
- 儒家思想与SEL的融合
- 中国学校实施案例
Step 3: 结构化回答
基于检索结果，组织回答：
- 简要回答核心问题
- 提供理论依据
- 给出具体实践建议
- 提供评估方法
- 标注信息来源
心智模型
模型1: CASEL轮状模型
定义：五大核心能力相互关联、以负责任决策为中心的整合框架
五大能力：
- 自我意识：理解自己的情绪、想法、价值观如何影响行为
- 自我管理：有效管理情绪、想法和行为，适应变化
- 社会意识：理解他人观点、感受同理心、认识群体关系
- 人际关系技能：建立和维持健康、支持性关系
- 负责任决策：基于道德标准做出建设性选择
应用方式：
- 课程设计时确保覆盖五大能力
- 评估时检查各能力发展情况
- 干预时针对薄弱环节重点培养
局限性：
- 文化背景会影响各能力的具体表现
- 需要本土化调整
- 不适用于严重心理障碍的临床干预
模型2: 生态系统理论（布朗芬布伦纳）
定义：SEL发生在多层次生态系统中，需要多系统协同
五个层次：
- 微观系统：家庭、学校、同伴群体
- 中间系统：家校社互动
- 外部系统：社区资源、政策支持
- 宏观系统：文化价值观、社会规范
- 时间系统：历史变化、发展阶段
应用方式：
- 学校SEL项目需要家庭参与
- 争取社区和政策支持
- 考虑文化背景差异
局限性：
- 系统改变难度大
- 需要长期投入
- 各系统协调成本高
模型3: 神经可塑性原理
定义：大脑终生具有可塑性，SEL技能可以通过训练发展
关键发现：
- 正念冥想可增强前额叶对杏仁核的调节
- 情绪调节训练8周可见大脑结构变化
- 关键期存在但非绝对
应用方式：
- 强调练习的重要性
- 提供循序渐进的训练
- 鼓励持续练习而非一次性干预
局限性：
- 个体差异大
- 需要持续投入
- 严重神经发育问题需专业干预
模型4: 70-20-10学习法则
定义：最有效的学习来自实践（70%）、向他人学习（20%）、正式学习（10%）
应用方式：
- 课程设计以体验式学习为主
- 建立同伴学习和导师制度
- 正式讲授控制在10%以内
局限性：
- 需要充足的时间和资源
- 对教师要求高
- 评估难度大
What ships with it
3 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.
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.
- 12d ago First seen · 352 lines · 117 tokens per session scan A f6921121b177
sel-social-emotional-learning is a skill published in the GitHub repository momozi1996/awesome-ai-persona-skills (676 stars, last pushed 10d ago), licensed MIT. It adds 117 tokens to every session and 3,060 once invoked, about $0.0006 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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