Borrowing it
Nothing to install: this file belongs to huifer/claude-code-interview. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/huifer/claude-code-interview/main/.claude/commands/company/add.mdgit clone --depth 1 https://github.com/huifer/claude-code-interviewWrote 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/commands/huifer/claude-code-interview/add)<a href="https://agentmods.dev/commands/huifer/claude-code-interview/add"><img src="https://agentmods.dev/badge/commands/huifer/claude-code-interview/add/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/commands/huifer/claude-code-interview/add"><img src="https://agentmods.dev/badge/commands/huifer/claude-code-interview/add.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 | $0.00015 | $0.02283 |
| Opus 5.5 | $0.00006 | $0.00913 |
| Sonnet 5.5 | $0.00003 | $0.00457 |
| Haiku 4.5 | $0.00002 | $0.00228 |
Grade A, and why
add 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 2mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- jd — 95% identical, 367 lines differ
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.
添加公司信息
添加 $ARGUMENTS 到您的求职列表,完整保存职位描述(JD)信息。
收集步骤
1. 公司基本信息
请提供以下信息:
必填:
- 公司名称: $ARGUMENTS
- 行业(如:Technology, Finance, Healthcare)
- 公司官网
可选:
- 总部地点
- 公司规模(如:100-500, 1000-5000, 10000+)
- 公司类型(如:Public, Private, Startup)
2. 目标职位信息
请提供您申请的职位信息:
- 职位ID(自动生成或手动指定,如:pos_001)
- 职位名称(如:Software Engineer III)
- 职位级别(如:L4, Senior, Principal)
- 工作地点
- 团队/部门
- 职位状态(如:preparing, applied, interviewing)
3. 职位描述(JD)- 重要!⭐
这是最重要的部分!我们将完整保存JD文本。
JD信息收集
请提供以下JD信息:
完整JD文本 (必填): 您可以通过以下方式提供:
- 直接粘贴 - 复制完整JD文本粘贴到这里
- 上传文件 - 提供包含JD的文件路径
- JD链接 - 提供在线JD链接,我将帮您读取
JD来源 (可选):
- 公司官网
- 招聘网站(如:拉勾、Boss直聘)
- 内推
- 其他
JD文本应包含:
- ✅ 职位概述
- ✅ 职责描述
- ✅ 技能要求(必需和优先)
- ✅ 资格要求(教育和经验)
- ✅ 加分项
- ✅ 福利待遇(可选)
JD保存方式
系统将:
- 保存完整JD原文 到
raw_text字段 - 记录JD来源 到
description_source字段 - 记录抓取时间 到
scraped_at字段 - 使用 jd-analyzer Skill 分析JD
- 提取结构化信息 到
structured_analysis - 评估匹配度 到
skill_match_analysis
4. 自动分析
收集完信息后,我将:
- 创建
data/companies/$ARGUMENTS.json文件 - 保存完整JD原文
- 使用 jd-analyzer Skill 分析JD
- 提取关键技能和要求
- 评估与您简历的匹配度
- 生成结构化分析报告
5. 输出报告
✅ 公司信息已保存: data/companies/$ARGUMENTS.json
📄 JD信息已保存:
- JD来源: LinkedIn
- 保存时间: 2025-01-09 14:30:00
- JD长度: 2,456 字符
📊 JD分析结果
## 关键技能
**必需** (7项):
- Python (expert)
- Distributed Systems (advanced)
- Cloud Computing (advanced)
- ...
**优先** (4项):
- Kubernetes (基础)
- Machine Learning (中级)
- ...
**加分** (3项):
- 开源贡献
- 技术博客
- ...
## 匹配度分析
✅ 完全匹配: 7项
⚠️ 部分匹配: 3项
❌ 缺失: 2项
**总体匹配度**: 75/100
**评估**:
- 技术栈匹配度高
- 需要加强Kubernetes
- 建议学习C++基础
## 下一步建议
1. /resume/variant $ARGUMENTS - 创建定制简历
2. /interview/prep $ARGUMENTS - 生成面试准备指南
3. /question/generate $ARGUMENTS - 生成面试题库
JD信息存储结构
保存的公司JSON将包含完整的JD信息:
{
"company_id": "google",
"basic_info": {...},
"target_positions": [
{
"position_id": "pos_001",
"title": "Software Engineer III",
"level": "L4",
"location": "Beijing, China",
"team": "Cloud Platform",
"status": "applied"
}
],
"job_descriptions": {
"pos_001": {
"title": "Software Engineer III, Cloud Platform",
"description_source": "https://linkedin.com/jobs/...",
"scraped_at": "2025-01-09T14:30:00Z",
"raw_text": "Google is looking for software engineers...
Minimum qualifications:
- Bachelor's degree in Computer Science or equivalent
- 3 years of experience in software development
with knowledge of one or more of the following: Python, Java, C++
...
Preferred qualifications:
- Master's degree or PhD
- 5 years of experience in distributed systems
...",
"structured_analysis": {
"required_skills": [
"Python",
"Java",
"C++",
"Distributed Systems"
],
"preferred_skills": [
"Kubernetes",
"Machine Learning",
"Data Engineering"
],
"responsibilities": [
"Design, develop, test, deploy, maintain and improve software",
"Manage individual project priorities, deadlines and deliverables"
],
"minimum_qualifications": [
"Bachelor's degree in Computer Science or equivalent",
"3 years of experience in software development"
],
"preferred_qualifications": [
"Master's degree or PhD",
"5 years of experience in distributed systems"
]
},
"skill_match_analysis": {
"matched_skills": [
{"skill": "Python", "proficiency": "expert"},
{"skill": "Distributed Systems", "proficiency": "advanced"}
],
"partial_match_skills": [
{"skill": "Java", "proficiency": "intermediate", "required": "advanced"}
],
"missing_skills": [
{"skill": "C++", "action": "需要学习基础"}
]
}
}
}
}
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.
- 2mo ago First seen · 330 lines · 15 tokens per session scan A 0d343a43b797
add is a command published in the GitHub repository huifer/claude-code-interview (27 stars, last pushed 10mo ago), licensed MIT. It adds 15 tokens to every session and 2,283 once invoked, about $0.0001 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.
add compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| addhuifer/claude-code-interview | Command | 27 | 10mo ago | MIT | A | 15 | Claude Code |
| wsdanielmiessler/LifeOS | Command | 20k | yesterday | MIT | A | 0 | Claude Code |
| cancel-ralphanthropics/claude-plugins-official | Command | 46k | yesterday | Apache-2.0 | A | 4 | Claude Code |
| engage.actionshypnguyen1209/offensive-claude | Command | 412 | 15d ago | MIT | A | 11 | Claude Code |
| focusData-Wise/claude-plugins | Command | 7 | yesterday | MIT | A | 0 | Claude Code |
| stuckData-Wise/claude-plugins | Command | 7 | yesterday | MIT | A | 0 | Claude Code |
| quickstartorq-ai/assistant-plugins | Command | 6 | 2d ago | MIT | A | 23 | Claude Code |