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 college-data-analysisgit 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/college-data-analysis)<a href="https://agentmods.dev/skills/hezkvectory/hermes-edu-skills/college-data-analysis"><img src="https://agentmods.dev/badge/skills/hezkvectory/hermes-edu-skills/college-data-analysis/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/college-data-analysis"><img src="https://agentmods.dev/badge/skills/hezkvectory/hermes-edu-skills/college-data-analysis.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 | $0.00058 | $0.01255 |
| Opus 5.5 | $0.00023 | $0.00502 |
| Sonnet 5.5 | $0.00012 | $0.00251 |
| Haiku 4.5 | $0.00006 | $0.00126 |
Grade A, and why
college-data-analysis 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 1mo 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
数据分析 Skill
把数据分析学习从工具教程变成业务问题、数据清洗、可视化、结论和报告表达。核心不是再推荐一堆资料，而是让用户今天能完成一个可检查的小成果。
这个 Skill 解决什么问题 / Problem
把数据分析学习从工具教程变成业务问题、数据清洗、可视化、结论和报告表达。核心不是再推荐一堆资料，而是让用户今天能完成一个可检查的小成果。
最适合 / Best For
- 学习 Excel/Python/SQL 数据分析
- 想做作品集项目
- 需要把分析结果讲清楚
- 业务同学提升数据思维
不适合 / Not For
- 伪造数据或操纵结论
- 只追求图表好看不回答问题
- 处理隐私数据而不脱敏
使用前请准备 / Inputs
- 分析目标
- 数据字段或样例
- 工具偏好
- 希望输出的报告形式
- 可选：业务背景和受众
推荐工作流 / Recommended Workflow
- 先把问题改写成可分析指标。
- 检查数据字段和缺失风险。
- 设计清洗、探索、图表和结论。
- 最后生成面向受众的报告结构。
输出格式 / Output Format
- 业务问题
- 指标设计
- 数据清洗清单
- 分析步骤
- 图表建议
- 结论表达
质量检查 / Quality Checks
- 结论必须回到问题
- 不能编造数据
- 要提示隐私脱敏
- 图表要服务判断而不是装饰
没有平台工具时 / Standalone Fallback
- 没有真实数据时，用模拟字段演示流程。
- 没有工具环境时，输出 SQL/Python/表格思路。
示例提示 / Example Prompts
- 我想做一个销售数据分析作品集，请帮我设计项目和报告。
- 这张表有这些字段，帮我找可以分析的问题。
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：
- 职业技能
适用角色：
- 学习者
调用信号 / Invocation Signals
意图：
college_data_analysiscareer_learning职业技能
示例表达：
- 开始数据分析 Skill
- 帮我做职业技能
- 根据当前上下文执行数据分析 Skill
公开 Skill 契约 / Public Skill Contract
- Workflow:
college_data_analysis.run - Category:
career-learning - Stages:
college,adult - Subjects:
计算机 - Abilities:
数据分析 - Quality Tier:
curated - Standalone Support:
needs_user_input - Public Release:
recommended - Requires Tools:
context.load,entitlement.check,workflow.create,report.aggregate_metrics,memory.write - Requires Data:
分析目标,数据字段或样例,工具偏好,希望输出的报告形式,可选：业务背景和受众 - 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:
大学,考研 - Semesters:
模块,模块 - Scenarios:
职业技能 - 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。
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.
- 1mo ago First seen · 144 lines · 58 tokens per session scan A 4ae1f38b368f
college-data-analysis is a skill published in the GitHub repository hezkvectory/hermes-edu-skills (122 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 1,255 once invoked, about $0.0002 per session on Opus 5.5. 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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