add

An interactive command for adding a company and a job to a job-search list while saving the full original job description.

In plain words
What is it for?
Use it to record a company and position, save a job description from pasted text, a file, or a link, and create structured skill and resume-match analyses.
Why use it?
It keeps company, role, source, and application details together instead of leaving important job-description text scattered across notes or links.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/huifer/claude-code-interview/add
Clone the repo
git clone --depth 1 https://github.com/huifer/claude-code-interview

Made for: Claude Code.

Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,283 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.02283
Opus 5 $0.00008 $0.01141
Sonnet 5 $0.00003 $0.00457
Haiku 4.5 $0.00002 $0.00228

Measured 2d ago against content hash 0d343a43b797, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • jd — 95% identical, 367 lines differ
.claude/commands/company/add.md · 330 lines

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:

  1. 直接粘贴 - 复制完整JD文本粘贴到这里
  2. 上传文件 - 提供包含JD的文件路径
  3. JD链接 - 提供在线JD链接,我将帮您读取

JD来源 (可选):

  • LinkedIn
  • 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:

  1. 保存完整JD原文raw_text 字段
  2. 记录JD来源description_source 字段
  3. 记录抓取时间scraped_at 字段
  4. 使用 jd-analyzer Skill 分析JD
  5. 提取结构化信息structured_analysis
  6. 评估匹配度skill_match_analysis

4. 自动分析

收集完信息后,我将:

  1. 创建 data/companies/$ARGUMENTS.json 文件
  2. 保存完整JD原文
  3. 使用 jd-analyzer Skill 分析JD
  4. 提取关键技能和要求
  5. 评估与您简历的匹配度
  6. 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"}
        ]
      }
    }
  }
}

Read the full file on GitHub · 330 lines

Changes

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.

  1. 2d ago First seen · 330 lines · 15 tokens per session scan A 0d343a43b797

Subscribe to this mod's changes

add 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 2,283 once invoked, about $0.0001 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.