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 hezkvectory/hermes-edu-skills --skill agent-learning-habitgit clone --depth 1 https://github.com/hezkvectory/hermes-edu-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/hezkvectory/hermes-edu-skills/agent-learning-habit)<a href="https://agentmods.dev/skills/hezkvectory/hermes-edu-skills/agent-learning-habit"><img src="https://agentmods.dev/badge/skills/hezkvectory/hermes-edu-skills/agent-learning-habit/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/hezkvectory/hermes-edu-skills/agent-learning-habit"><img src="https://agentmods.dev/badge/skills/hezkvectory/hermes-edu-skills/agent-learning-habit.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00042 | $0.01265 |
| Opus 5 | $0.00021 | $0.00633 |
| Sonnet 5 | $0.00008 | $0.00253 |
| Haiku 4.5 | $0.00004 | $0.00127 |
Grade A, and why
agent-learning-habit 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
学习习惯 Skill
把抽象的“养成学习习惯”落到固定触发、最小动作、即时反馈和家庭协作上。
这个 Skill 解决什么问题 / Problem
把抽象的“养成学习习惯”落到固定触发、最小动作、即时反馈和家庭协作上。
最适合 / Best For
- 每日打卡坚持不了
- 作业前磨蹭
- 复习订正总忘记
- 家长想减少催促
不适合 / Not For
- 用打卡制造焦虑
- 把所有问题归咎于孩子不自律
使用前请准备 / Inputs
- 想养成的习惯
- 孩子年级
- 每天可用时间
- 当前阻力
- 家长能提供的支持
推荐工作流 / Recommended Workflow
- 选择一个最小习惯
- 绑定固定触发点
- 设计 3 分钟启动动作
- 设置可见反馈
- 每周复盘一次并调整难度
输出格式 / Output Format
- 习惯目标
- 触发点
- 最小行动
- 家长话术
- 打卡表
- 复盘问题
质量检查 / Quality Checks
- 一次只改一个习惯
- 动作必须小到能开始
- 反馈不能只看分数
- 要允许中断后恢复
没有平台工具时 / Standalone Fallback
- 没有打卡工具时，输出纸面记录表。
- 没有家庭数据时，用用户描述的阻力开始设计。
示例提示 / Example Prompts
- 帮孩子建立每天 15 分钟阅读习惯，不要太复杂。
- 孩子总忘记订正错题，帮我设计一个能坚持的流程。
适用场景 / When To Use
当学习者、家长、老师、学校或教育应用开发者需要处理以下场景时，可以使用这个 Skill。
最适合的场景：
- 每日打卡
适用角色：
- 学习者
- 家长
- 老师
调用信号 / Invocation Signals
意图：
agent_learning_habitlearning_core每日打卡
示例表达：
- 开始学习习惯 Skill
- 帮我做每日打卡
- 根据当前上下文执行学习习惯 Skill
公开 Skill 契约 / Public Skill Contract
- Workflow:
agent_learning_habit.run - Category:
learning-core - Stages:
primary,junior,senior - Subjects:
学习能力 - Abilities:
习惯培养 - Quality Tier:
curated - Standalone Support:
needs_user_input - Public Release:
recommended - Requires Tools:
context.load,entitlement.check,workflow.create,memory.write - Requires Data:
学习目标,年级或水平,用户输入的题目/记录/上下文 - Export Mode:
installable - Release Channel:
recommended
成熟度备注：
- 已按精品 Skill 标准补充边界、输入、工作流、输出格式和示例。
参数化使用 / Parameters
这个 Skill 不再把年级、册别、单元、知识点和难度拆成大量独立 Skill。请在调用时通过参数或自然语言补充这些信息。
- Grades:
一年级,二年级,三年级,四年级,五年级,六年级,七年级,八年级,九年级,高一,高二,高三 - Semesters:
上册,下册,上册,下册,必修一,必修二,选择性必修 - Scenarios:
每日打卡 - Difficulties:
基础,标准,提高 - Parameterized Dimensions:
grade,semester,unit,lesson,knowledgePointCodes,scenario,difficulty
独立 Hermes 使用方式 / Standalone Hermes Usage
这个 Skill 可以通过 Hermes 的 skills.external_dirs 作为外部 Skill 加载。
如果你有自己的工具、记忆、课程数据或 workflow runner，可以把它们与本 Skill 组合使用。如果没有外部工具，也可以直接使用上面的说明来引导对话，生成有用的学习或教学反馈。
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 · 146 lines · 42 tokens per session scan A 3048a47311f7
agent-learning-habit is a skill published in the GitHub repository hezkvectory/hermes-edu-skills (94 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 1,265 once invoked, about $0.0002 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.
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