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 agentmods add commands/huifer/claude-code-interview/importgit clone --depth 1 https://github.com/huifer/claude-code-interviewWhat 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 | $0.00015 | $0.02082 |
| Opus 5 | $0.00008 | $0.01041 |
| Sonnet 5 | $0.00003 | $0.00416 |
| Haiku 4.5 | $0.00002 | $0.00208 |
Grade B, and why
import scanned grade B with 1 finding 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 2d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt-get install pandoc How it starts
The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
导入现有简历
从 $ARGUMENTS 导入您的现有简历。
支持的格式
1. Markdown (.md) - 推荐 ✅
最简单的方式
- 直接读取内容
- 保持格式
- 易于编辑
2. PDF (.pdf)
需要转换工具
- 使用PDF读取工具提取文本
- 保留基本结构
- 可能需要手动调整
3. Word (.docx)
需要转换工具
- 使用pandoc转换为Markdown
- 或使用其他文档处理工具
- 保留基本格式
工作流程
步骤 1: 读取文件
根据文件类型:
- Markdown: 直接使用Read工具读取
- PDF: 使用PDF读取工具提取文本
- Word: 使用pandoc转换为Markdown后读取
步骤 2: 解析内容
提取以下信息:
- 个人信息(姓名、联系方式)
- 专业总结
- 技能列表
- 工作经历
- 项目经验
- 教育背景
- 认证证书
步骤 3: 转换为JSON
将提取的信息转换为 data/resume/base.json 格式
步骤 4: 验证和编辑
- 显示提取的信息供用户确认
- 标记可能需要手动编辑的部分
- 允许用户补充缺失信息
步骤 5: 保存
- 保存到
data/resume/base.json - 显示导入报告
使用方法
方式 1: Markdown简历(最简单)
/resume/import /path/to/resume.md
方式 2: PDF简历
/resume/import ~/Documents/my_resume.pdf
系统将:
- 读取PDF内容
- 提取文本信息
- 解析结构
- 生成JSON
方式 3: Word简历
/resume/import ~/Documents/my_resume.docx
系统将:
- 使用pandoc转换为Markdown
- 读取转换后的内容
- 解析结构
- 生成JSON
检测的简历结构
Markdown格式示例
# 张三
邮箱: [email protected]
电话: +86 138-0000-0000
LinkedIn: linkedin.com/in/zhangsan
GitHub: github.com/zhangsan
## 专业总结
资深软件工程师,专注于分布式系统和机器学习...
## 技能
### 编程语言
- Python (专家)
- Java (熟练)
- JavaScript (熟练)
### 框架
- React
- Spring Boot
- Django
## 工作经历
### 高级软件工程师 | ABC科技公司 | 2020.06 - 至今
负责核心微服务架构设计和开发...
**成就**:
- 设计并实现高并发订单处理系统,处理能力提升300%
- 领导5人团队完成微服务迁移项目
- 优化数据库查询性能,响应时间降低50%
**技术栈**: Java, Spring Cloud, Redis, MySQL, Docker
### 软件工程师 | XYZ互联网 | 2018.07 - 2020.05
参与电商平台开发...
## 项目经验
### 分布式任务调度系统 | 创始人 | 2022.01 - 至今
GitHub: github.com/zhangsan/task-scheduler
一个可扩展的任务调度框架...
**成就**:
- GitHub stars 1k+
- 被3家公司用于生产环境
**技术**: Go, gRPC, Etcd, Docker
## 教育背景
### 计算机科学硕士 | 清华大学 | 2016.09 - 2018.06
GPA: 3.8/4.0
**荣誉**: 优秀毕业生、国家奖学金
**课程**: 分布式系统、机器学习、高级算法
### 计算机科学学士 | 北京大学 | 2012.09 - 2016.06
GPA: 3.7/4.0
**荣誉**: 一等奖学金
PDF/Word处理
PDF读取
对于PDF文件,尝试:
- 读取PDF文本内容
- 识别章节标题
- 提取关键信息
- 重建结构
注意: PDF格式解析可能不完美,建议:
- 使用清晰的PDF模板
- 检查导入结果
- 手动调整缺失部分
Word转换
对于Word文件,使用pandoc:
pandoc input.docx -o temp.md
然后读取转换后的Markdown文件。
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.
- 2d ago First seen · 330 lines · 15 tokens per session scan B 087a5c578dcc
import is a command published in the GitHub repository huifer/claude-code-interview (23 stars, last pushed 7mo ago), licensed MIT. It adds 15 tokens to every session and 2,082 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.