能力标签
智能求职助手
🛠
AI工具

智能求职助手

基于 JavaScript · 开源 AI 工具,GitHub 社区精选
英文名:career-ops
⭐ 44.3k Stars 🍴 9.3k Forks 💻 JavaScript 📄 MIT 🏷 AI 8.2分
8.2AI 综合评分
AI智能体工作流自动化求职系统Claude职业发展
✦ AI Skill Hub 推荐

AI Skill Hub 强烈推荐:智能求职助手 是一款优质的AI工具。在 GitHub 上收获超过 44.3k 颗 Star,AI 综合评分 8.2 分,在同类工具中表现稳健。如果你正在寻找可靠的AI工具解决方案,这是一个值得深入了解的选择。

📚 深度解析

智能求职助手 是一款基于 JavaScript 的开源工具,在 GitHub 上收获 44k+ Star,是AI智能体、工作流自动化、求职系统、Claude领域中的优质开源项目。开源工具的最大优势在于代码完全透明,你可以审计每一行代码的安全性,也可以根据自身需求进行二次开发和定制。

**为什么要使用开源工具而非商业 SaaS?**
对于个人开发者和有隐私需求的用户,本地部署的开源工具意味着数据不离本机,不受第三方服务商的数据政策约束。同时,开源工具通常没有使用次数限制和月度费用,一次安装即可长期使用,对于高频使用场景的总拥有成本(TCO)远低于订阅制商业工具。

**安装与环境准备**
智能求职助手 依赖 JavaScript 运行环境。建议通过 pyenv(Python)或 nvm(Node.js)管理 JavaScript 版本,避免全局环境污染。对于新手用户,推荐先创建虚拟环境(python -m venv venv && source venv/bin/activate),再安装依赖,这样即使出现问题也可以随时删除虚拟环境重新开始,不影响系统稳定性。

**社区与维护**
GitHub Issue 和 Discussion 是获取帮助的最快渠道。在提问前建议先检查 Closed Issues(已关闭的问题),大多数常见问题都已有解答。遇到 Bug 时,提供 pip list 的输出、完整错误堆栈和最小可复现示例,能显著提高开发者响应速度。AI Skill Hub 将持续追踪 智能求职助手 的版本更新,及时通知重要功能变化。

📋 工具概览

基于Claude AI的开源求职系统,整合14种技能模式和Go语言仪表板,自动化处理职位搜索、简历优化、面试准备等环节。适合求职者、HR和职业发展从业者提升求职效率。

智能求职助手 是一款基于 JavaScript 开发的开源工具,专注于 AI智能体、工作流自动化、求职系统 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。

GitHub Stars
⭐ 44.3k
开发语言
JavaScript
支持平台
Windows / macOS / Linux
维护状态
活跃维护,更新频繁
开源协议
MIT
AI 综合评分
8.2 分
工具类型
AI工具
Forks
9.3k

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

基于Claude AI的开源求职系统,整合14种技能模式和Go语言仪表板,自动化处理职位搜索、简历优化、面试准备等环节。适合求职者、HR和职业发展从业者提升求职效率。

智能求职助手 是一款基于 JavaScript 开发的开源工具,专注于 AI智能体、工作流自动化、求职系统 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。

📌 核心特色
  • 开源免费,支持本地部署,数据完全自主可控
  • 活跃的 GitHub 开源社区,持续迭代更新
  • 提供详细文档和使用示例,新手友好
  • 支持自定义配置,灵活适配不同使用环境
  • 可作为基础组件集成进现有技术栈或进行二次开发
🎯 主要使用场景
  • 本地部署运行,保护数据隐私,满足合规要求
  • 自定义集成到现有系统,扩展技术栈能力
  • 作为开源基础组件进行商业化二次开发
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:npm 全局安装
npm install -g career-ops

# 方式二:npx 直接运行(无需安装)
npx career-ops --help

# 方式三:项目依赖安装
npm install career-ops

# 方式四:从源码运行
git clone https://github.com/santifer/career-ops
cd career-ops
npm install
npm start
📋 安装步骤说明
  1. 访问 GitHub 仓库页面
  2. 按照 README 文档完成依赖安装
  3. 根据系统环境完成初始化配置
  4. 参考官方示例或文档开始使用
  5. 遇到问题可在 GitHub Issues 中查找解答
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 命令行使用
career-ops --help

# 基本用法
career-ops [options] <input>

# Node.js 代码中使用
const career_ops = require('career-ops');

const result = await career_ops.run(options);
console.log(result);
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
# career-ops 配置说明
# 查看配置选项
career-ops --config-example > config.yml

# 常见配置项
# output_dir: ./output
# log_level: info
# workers: 4

# 环境变量(覆盖配置文件)
export CAREER_OPS_CONFIG="/path/to/config.yml"
📑 README 深度解析 真实文档 完整度 90/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

简介

English | Español | Deutsch | Français | Português (Brasil) | 한국어 | 日本語 | 简体中文 | 繁體中文 | Українська | Русский | Polski | Dansk | தமிழ் | العربية | हिन्दी | Türkçe

</div>

<p align="center"> <a href="https://x.com/santifer"><img src="docs/hero-banner.jpg" alt="career-ops Multi-Agent Job Search System" width="800"></a> </p>

<p align="center"> <em>I spent months applying to jobs the hard way. So I engineered the system I wish I had.</em><br> Companies use AI to filter candidates. <strong>I just gave candidates AI to <em>choose</em> companies.</strong><br> <em>Now it's open source.</em> </p>

<hr>

<p align="center"> <a href="HIRED.md"><img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fraw.githubusercontent.com%2Fsantifer%2Fcareer-ops%2Fmain%2Fdocs%2Fhired-count.json&query=%24.count&label=%F0%9F%8E%89%20HIRED%20WITH%20CAREER-OPS&suffix=%20verified&color=2ea44f&style=for-the-badge&labelColor=2b3137" alt="Hired with career-ops: verified count"></a> </p>

<p align="center"><sub>Landed yours? <a href="https://github.com/career-ops-hq/career-ops/issues/new?template=i-got-hired.yml">Share it →</a> · your card shows someone mid-search that the way out exists.</sub></p>

<p align="center"> <a href="HIRED.md"><img src="docs/hired-wall.svg" alt="The three most recent hired stories" width="800"></a> </p>

<p align="center"><sub>Every count is a public story you can <a href="HIRED.md">audit →</a> · every one of them started where you are now.</sub></p>

<p align="center"> <a href="https://trendshift.io/repositories/25195" target="_blank" rel="noopener noreferrer"><img src="https://trendshift.io/api/badge/repositories/25195" alt="santifer%2Fcareer-ops | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> </p>

<p align="center"> <a href="https://www.producthunt.com/products/santifer-io?utm_source=badge-featured&utm_medium=badge" target="_blank" rel="noopener noreferrer"><img src="docs/press/producthunt.svg" alt="career-ops on Claude | Product Hunt" style="width: 206px; height: 54px; vertical-align: middle;" width="206" height="54"/></a> </p>

<p align="center"><sub>FEATURED IN</sub></p>

<p align="center"> <a href="https://wired.com.gr/article/to-ai-ergaleio-pou-fernei-epanastasi-ston-tropo-pou-psachnoume-douleia/" rel="noopener noreferrer nofollow"><picture><source media="(prefers-color-scheme: dark)" srcset="docs/press/wired-dark.svg"><img src="docs/press/wired.svg" alt="WIRED" height="32"></picture></a> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <a href="https://www.businessinsider.com/how-i-built-tool-filter-job-listings-landed-head-ai-2026-4" rel="noopener noreferrer nofollow"><picture><source media="(prefers-color-scheme: dark)" srcset="docs/press/business-insider-dark.svg"><img src="docs/press/business-insider.svg" alt="Business Insider" height="32"></picture></a> </p>

---

<p align="center"> <img src="docs/demo.gif" alt="career-ops Demo" width="800"> </p>

<p align="center"><strong>740+ job listings evaluated · 100+ personalized CVs · 1 dream role landed</strong></p>

<p align="center"><sub>Created and maintained by <a href="https://santifer.io">Santiago Fernández de Valderrama Aparicio</a> (<a href="https://github.com/santifer">@santifer</a>)</sub></p>

<p align="center"> <a href="https://warpchart.dev/hq"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://warpchart.dev/api/chart?theme=dark&v=3"> <img alt="Live star telemetry of career-ops-hq/career-ops" src="https://warpchart.dev/api/chart?theme=light&v=3" loading="lazy"> </picture> </a> </p>

<p align="center"> <a href="https://discord.gg/8pRpHETxa4"><img src="https://img.shields.io/badge/Join_the_community-Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white" alt="Discord"></a> </p>

<p align="center"> <a href="https://github.com/career-ops-hq/career-ops/releases/latest"><img src="https://img.shields.io/npm/v/%40santifer%2Fcareer-ops?style=for-the-badge&labelColor=2b3137&color=2ea44f&label=release" alt="Latest release"></a> </p>

<p align="center"> <a href="https://claude.com/claude-code"><img src="https://img.shields.io/badge/Built_with-Claude_Code-000?style=for-the-badge&logo=anthropic&logoColor=white" alt="Built with Claude Code"></a> </p>

<p align="center"> <sub>Also runs on any agent-skill-standard CLI. See <a href="docs/SUPPORTED_CLIS.md">Supported CLIs</a>.</sub><br> <img src="https://img.shields.io/badge/Claude_Code-000?style=flat&logo=anthropic&logoColor=white" alt="Claude Code"> <img src="https://img.shields.io/badge/OpenCode-111827?style=flat&logo=terminal&logoColor=white" alt="OpenCode"> <img src="https://img.shields.io/badge/Antigravity_CLI-4285F4?style=flat&logo=google&logoColor=white" alt="Antigravity CLI"> <img src="https://img.shields.io/badge/Codex-412991?style=flat&logo=openai&logoColor=white" alt="Codex"> <img src="https://img.shields.io/badge/Qwen-615CED?style=flat" alt="Qwen"> <img src="https://img.shields.io/badge/Kimi-FF4B4B?style=flat" alt="Kimi"> <img src="https://img.shields.io/badge/GitHub_Copilot-000?style=flat&logo=githubcopilot&logoColor=white" alt="GitHub Copilot"> <img src="https://img.shields.io/badge/Grok_Build_CLI-000?style=flat&logo=x&logoColor=white" alt="Grok Build CLI"> <br> <img src="https://img.shields.io/badge/Node.js-339933?style=flat&logo=node.js&logoColor=white" alt="Node.js"> <img src="https://img.shields.io/badge/Go-00ADD8?style=flat&logo=go&logoColor=white" alt="Go"> <img src="https://img.shields.io/badge/Playwright-2EAD33?style=flat&logo=playwright&logoColor=white" alt="Playwright"> <img src="https://img.shields.io/badge/Bubble_Tea-FF75B5?style=flat&logo=go&logoColor=white" alt="Bubble Tea"> <img src="https://img.shields.io/badge/License-MIT-blue.svg" alt="MIT"> <a href="TRADEMARK.md"><img src="https://img.shields.io/badge/Trademark-Policy-blue.svg" alt="Trademark Policy"></a> </p>

3. Evaluate a job description

node gemini-eval.mjs "We are looking for a Senior AI Engineer..." node gemini-eval.mjs --file ./jds/my-job.txt node agent-inbox.mjs add "..." # queue a request for the next session npm run gemini:eval -- "JD text here" ```

Free tier: Both options work without billing. Native CLI uses Google OAuth; the API script uses gemini-3.6-flash (rate limits are model- and tier-dependent; see Google AI docs for current quotas).

About the Author

I'm Santiago Fernández de Valderrama Aparicio (santifer) -- Head of Applied AI, former founder (built and sold a business that still runs with my name on it). I built career-ops to manage my own job search. It worked: I used it to land my current role.

Curious how this repo is maintained in ~4 hours a week? Read Agentic maintenance: how career-ops is run by a fleet of AI agents.

My portfolio and other open source projects → santifer.io

Wikidata: Santiago Fernández de Valderrama Aparicio · career-ops.

Features

FeatureDescription
**Auto-Pipeline**Paste a URL, get a full evaluation + PDF + tracker entry
**A-H Evaluation**Role summary, CV match (with how much each requirement matters for this posting, and whether that weight came from the JD's own wording, its structure, or an estimate — labelled per requirement, and an estimate can never be top-band), level strategy, comp research, personalization, interview prep (STAR+R) -- plus a Block G posting-legitimacy check that flags scams and ghost jobs, and a Work-Auth signal that flags an explicit no-sponsorship JD as a hard blocker
**Interview Story Bank**Accumulates STAR+Reflection stories across evaluations -- 5-10 master stories that answer any behavioral question
**Negotiation Scripts**Salary negotiation frameworks, geographic discount pushback, competing offer leverage
**ATS PDF Generation**Keyword-injected CVs with Space Grotesk + DM Sans design
**Cover Letter Generator**Research-backed cover letters with keyword mirroring, four interactive angle prompts (why/problems/approach/tone), draft-in-chat approval gate, and A4 PDF via the same HTML + Playwright pipeline as CVs. Auto-drafts on every evaluation; complete and generate on demand via /career-ops cover
**Application Email Drafts**Formal recruiter/referral/cold application emails from a report or pasted JD, with subject line, attachment checklist, source-backed fit points, and a profile-driven contact block. Draft-only -- career-ops never sends, submits, or clicks anything.
**Portal Scanner**100+ companies pre-configured (Anthropic, OpenAI, ElevenLabs, Retool, n8n...) + custom queries across Ashby, Greenhouse, Lever, Wellfound
**Funded Company Discovery**Review-first company:funded command surfaces recently funded companies and source diagnostics from structured public feeds without editing your data
**Batch Processing**Parallel evaluation with headless CLI workers (claude -p / opencode run)
**Dashboard TUI**Terminal UI to browse, filter, and sort your pipeline
**Human-in-the-Loop**AI evaluates and recommends, you decide and act. The system never submits an application -- you always have the final call
**Pipeline Integrity**Automated merge, dedup, status normalization, health checks
**Interview Suite**Time-blocked prep plans, practice sessions with feedback, post-interview debriefs ([interview/](modes/interview/README.md)), and a company red-flag detector ([interview-redflag](modes/interview-redflag.md))
**Offer Stage**Contract reading companion -- clause walk plus a lawyer question list ([offer-prep](modes/offer-prep.md)) -- and a desired/advertised/actual salary-gap analyzer (salary-gap.mjs)
**Follow-ups & Replies**Follow-up cadence calculator and seeded reminders (followup-cadence.mjs, followup-seed.mjs); employer reply classification into tracker updates ([reply-watch](modes/reply-watch.md))
**Pattern Analysis**Rejection patterns and per-ATS-channel advance rates (analyze-patterns.mjs), lifetime funnel stats (stats.mjs), repost/ghost-job detection (detect-reposts.mjs)
**Plugin System**Opt-in integrations (Gmail, Notion, Apify + a community registry), disabled by default -- see [docs/PLUGINS.md](docs/PLUGINS.md)
**Beyond the CV**Company research ([deep](modes/deep.md)) surfaces AI strategy, recent moves, engineering culture, and the angle your profile should take. Contact discovery ([contacto](modes/contacto.md)) identifies the hiring manager, recruiter, or team peer worth reaching out to and drafts a ≤300-character LinkedIn message tuned to each contact type. Formal application email drafts ([email](modes/email.md)) turn an evaluated report or pasted JD into a subject line, body, and attachment checklist without sending, submitting, or clicking anything. Applications get you in the queue; research gets you a conversation.

2. Install dependencies

npm install

2. Check setup

npm run doctor # Validates all prerequisites

Global install

npm i -g @santifer/career-ops

This installs the career-ops binary globally so you can run it directly instead of via npx. Unlike npx @santifer/career-ops init (which bootstraps a project directory), the global install gives you a persistent career-ops command available anywhere in your terminal.

Which one should you use? - npx @santifer/career-ops init — best for first use; creates a dedicated project folder. - npm i -g @santifer/career-ops — best once you have a project folder and want to run career-ops commands directly.

The system is designed to be customized by your AI coding CLI itself. Modes, archetypes, scoring weights, negotiation scripts -- just ask it to change them. It reads the same files it uses, so it knows exactly what to edit.

See docs/SETUP.md for the full setup guide, docs/RUNNING_ON_A_BUDGET.md for instructions on running career-ops cheaply using custom or local models (and docs/FREE_TIER.md for running it at zero cost on Antigravity CLI's free tier), docs/AUTOMATION.md for scheduling recurring scans and a zero-token triage-to-shortlist recipe, docs/APPLY_AUTOFILL.md for details on the ATS auto-fill flow, docs/LINKEDIN_JOIN.md for cross-referencing a LinkedIn connections export against the companies in your funnel, and docs/FAQ.md for answers to common setup questions, including how story provenance prevents invented numbers. Design principles live in ARCHITECTURE.md; runtime flows in docs/ARCHITECTURE.md.

Grok Build CLI Integration

career-ops supports Grok Build CLI natively, the same way it supports Claude Code and OpenCode. AGENTS.md is auto-loaded as project rules, and all slash commands are available through the shared skill entrypoint.

Native Grok Build CLI

```bash

Standalone Gemini API Script (No CLI install needed)

```bash

Quick Start

Fastest way — one command:

npx @santifer/career-ops init
💡 npx ships with Node.js — it runs the installer once, without installing anything globally. No Node yet? Install it first. (Already using a Claude Code / Gemini / Codex CLI? Then you already have it.)

This clones the latest release into ./career-ops and installs dependencies. Then:

cd career-ops
claude   # or codex / qwen / opencode / agy / grok — open your AI CLI here

On first launch, career-ops walks you through setup — your CV, profile and target roles — just by chatting. Nothing to edit by hand.

<details> <summary><b>Prefer to set it up manually? (git clone)</b></summary>

```bash git clone https://github.com/career-ops-hq/career-ops.git cd career-ops && npm install npx playwright install chromium # only needed for PDF generation

Usage

career-ops uses a shared command router. In CLIs that register slash commands, it looks like this:

/career-ops                → Show all available commands
/career-ops {paste a JD}   → Full auto-pipeline (evaluate + PDF + tracker)
/career-ops scan           → Scan portals for new offers
/career-ops pdf            → Generate ATS-optimized CV
/career-ops cover          → Cover letter generator (paste JD or /career-ops cover {slug})
/career-ops email          → Formal application email draft (draft-only; never sends, submits, or clicks)
/career-ops batch          → Batch evaluate multiple offers
/career-ops tracker        → View application status
/career-ops apply          → Fill application forms with AI
/career-ops outcome        → Record application outcome & archive artifacts
/career-ops pipeline       → Process pending URLs
/career-ops contacto       → Find hiring manager / recruiter / peer + draft a ≤300-char LinkedIn message per contact type
/career-ops deep           → Generate a structured 6-axis research prompt (AI strategy, recent moves, culture, challenges, competitors, candidate angle)
/career-ops training       → Evaluate a course/cert
/career-ops project        → Evaluate a portfolio project

Or just paste a job URL or description directly -- career-ops auto-detects it and runs the full pipeline.

In Codex, slash commands are not guaranteed. Use the same mode names in a prompt instead, or call them from codex exec.

3. Configure

cp config/profile.example.yml config/profile.yml # Edit with your details cp templates/portals.example.yml portals.yml # Customize companies

Edit .env, set GEMINI_API_KEY=your_key_here

Pre-configured Portals

The scanner comes with 100+ companies ready to scan and 45+ search queries across major job boards. Copy templates/portals.example.yml to portals.yml and add your own:

AI Labs: Anthropic, OpenAI, Mistral, Cohere, LangChain, Pinecone Voice AI: ElevenLabs, PolyAI, Parloa, Hume AI, Deepgram, Vapi, Bland AI AI Platforms: Retool, Airtable, Vercel, Temporal, Glean, Arize AI Contact Center: Ada, LivePerson, Sierra, Decagon, Talkdesk, Genesys Enterprise: Salesforce, Twilio, Gong, Dialpad LLMOps: Langfuse, Weights & Biases, Lindy, Cognigy, Speechmatics Automation: n8n, Zapier, Make.com European: Factorial, Attio, Tinybird, Clarity AI, Travelperk

Job boards searched: 55+ provider modules cover ATS APIs, board-wide feeds, XML/RSS feeds, markdown feeds, and local parsers. See Supported job boards for the full table.

By default node scan.mjs (a.k.a. npm run scan) trusts what each ATS feed returns. Some companies leave stale postings in their public API even after the role is closed, so those expired entries can leak into pipeline.md. Pass --verify to launch Playwright after the API pass and drop expired postings before they hit the pipeline:

node scan.mjs --verify          # zero-token discovery + Playwright liveness check

The verification is sequential and only runs against new offers (after dedup), so the cost stays bounded.

External Data Directory (Optional)

By default, user-layer data (such as cv.md, portals.yml, and data/ / reports/ / output/ folders) lives inside the project root folder.

To separate your personal data from the code (making it easier to switch branches, pull updates, or test multiple profiles), you can configure an external data directory using the following precedence:

1. Environment Variables: Set the CAREER_OPS_ROOT or CAREER_OPS_DATA_DIR environment variable:

   export CAREER_OPS_ROOT=~/my-career-data
   
2. Marker File: Create a .career-ops-data file in the repository root containing the path to your data directory. 3. Default: Defaults to the repository root.

Once resolved, all user files are resolved and written relative to that folder, while prompt files and scripts continue to resolve relative to the repository.

  • Tracker Override: You can also set CAREER_OPS_TRACKER to override the applications tracker file path directly.
  • Writes: All write operations (such as merges) canonically target {DATA_ROOT}/data/applications.md.

The Go dashboard TUI, Node.js scripts, and AI agent modes all automatically respect this resolution hierarchy.

5. Open your AI CLI in this directory

claude # or codex / opencode / qwen / agy / grok

Then ask your CLI to adapt the system to you:

If your CLI supports slash commands, use /career-ops (or its CLI-specific alias)

Antigravity CLI Integration

career-ops supports Antigravity CLI natively, the same way it supports Claude Code and OpenCode. All slash commands are available through the shared skill entrypoint, using the same modes/*.md evaluation logic.

Google has transitioned consumer Gemini CLI access to Antigravity CLI. GEMINI.md is now a no-op compatibility guard so Antigravity does not duplicate the full project instructions when it reads both AGENTS.md and GEMINI.md.

1. Get a free API key at https://aistudio.google.com/apikey

cp .env.example .env

Paste a job URL or JD text to trigger auto-pipeline

"Run the career-ops pipeline mode for data/pipeline.md"

Codex Integration

career-ops supports Codex through the same shared router, but the invocation model is different from CLIs that auto-register slash commands. For the full guide, see docs/CODEX.md.

FAQ

What is career-ops? career-ops is an open-source AI job search that runs locally in your AI coding CLI (Claude Code, Codex, OpenCode and others) and leaves every decision to you. It evaluates job offers against your CV, generates ATS-tailored PDFs, finds the right person to contact, and tracks everything in one place: you always have the final call. It is the first reference implementation of the CareerOps Manifesto. More at career-ops.org.

Can I run career-ops for free, or on a cheaper / local model? Yes. career-ops is CLI-agnostic and runs on free and local models — via OpenRouter free models, Ollama, or any OpenAI-compatible endpoint — so you are not tied to a paid subscription. See docs/RUNNING_ON_A_BUDGET.md for the full setup.

I pay for Claude Pro/Max but career-ops is burning API credits. Why? Because an ANTHROPIC_API_KEY in your environment takes precedence over your logged-in subscription: the CLI uses the key and bills per token. Run echo $ANTHROPIC_API_KEY, and if it prints anything, remove it from your shell profile, restart the terminal and run /login. Batch mode is the exception, since claude -p workers do not use the interactive login: run claude setup-token once and export the result as CLAUDE_CODE_OAUTH_TOKEN. Full walkthrough in docs/RUNNING_ON_A_BUDGET.md.

Which AI CLIs does career-ops work with? career-ops runs on any major AI coding CLI — Claude Code, Codex, Gemini / Antigravity, OpenCode, Grok, Qwen and more — through the open Agent Skill Standard, so it is never locked to a single vendor. Use the CLI you already have.

How do I install career-ops on Windows? career-ops runs on Windows. Platform-specific setup and the known sharp edges — Git Bash discovery, line endings, Task Scheduler — are in docs/WINDOWS.md. If skills fail to load with a symlink error during install, the fix is in docs/FAQ.md. Full steps are in docs/SETUP.md.

Does career-ops auto-apply to jobs for me? No. career-ops is a filter, not a spray-and-pray auto-applier. The AI evaluates, ranks and drafts; you review and decide. It never submits, sends, or clicks anything — you always have the final call. That human-in-the-loop design is the whole point.

Is career-ops free and open source? Yes. career-ops is free and open source, and for the candidate it always will be — it is the first reference implementation of the CareerOps Manifesto. Read it, and if it says what you believe, sign it.

🇨🇳 中文文档镜像 AI 翻译 2026-06-17
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介

Career-Ops 是一个基于 Multi-Agent(多智能体)架构的智能求职系统。该项目由资深 AI 专家 Santiago 开发,旨在通过自动化流程辅助求职者进行职位评估、简历优化及面试准备。它不仅能自动分析职位描述(JD),还能生成针对性的面试策略,帮助开发者在激烈的求职竞争中脱颖而出,实现高效、智能的职业转型。

⚡ 功能介绍

Career-Ops 提供了一套完整的自动化求职流水线。其核心功能包括:Auto-Pipeline 模式,只需粘贴职位 URL 即可自动完成职位评估、生成 PDF 报告并同步至追踪器;6-Block Evaluation 深度评估模块,涵盖职位总结、简历匹配度分析、职级策略、薪资调研、个性化内容生成以及基于 STAR+R 模型的面试准备,确保求职过程全方位覆盖。

📋 环境依赖

在使用 Career-Ops 之前,请确保您的开发环境已安装 Node.js 及 npm。此外,由于系统涉及 PDF 生成功能,需要通过 npx playwright 安装 chromium 浏览器内核。建议在运行前通过 npm run doctor 命令进行环境自检,以确保所有前置依赖项均已正确配置。

🛠 安装步骤(Docker/pip/源码)

首先,通过 git clone 克隆项目仓库并进入目录,执行 npm install 安装依赖,随后运行 npx playwright install chromium 以支持 PDF 生成。安装完成后,请务必运行 npm run doctor 进行环境校验。若需使用 Gemini CLI 功能,请通过 npm install -g @google/gemini-cli 进行全局安装。

🚀 使用教程

Career-ops 通过单斜杠命令进行交互,支持多种模式。使用 `/career-ops` 可查看所有可用命令;输入 `/career-ops {JD内容}` 可启动全自动流水线(评估+PDF+追踪器);`/career-ops scan` 用于扫描门户网站新职位;`/career-ops pdf` 用于生成针对 ATS 优化的简历;`/career-ops batch` 支持批量评估职位;`/career-ops tracker` 查看申请状态;`/career-ops apply` 则用于辅助填写申请表。

⚙️ 配置说明(含 MCP / env)

项目配置分为个人资料与模板两部分。首先需将 config/profile.example.yml 复制为 config/profile.yml 并编辑个人信息;同时将 templates/portals.example.yml 复制为 portals.yml 以自定义目标公司。对于 API 密钥配置,请将 .env.example 复制为 .env,并在其中设置 GEMINI_API_KEY。系统支持通过 Native Gemini CLI 进行集成,逻辑由 modes/*.md 驱动。

🔌 API 说明

Career-ops 原生支持 Gemini CLI 集成,其交互体验与 Claude Code 及 OpenCode 一致。系统内置了 15 种斜杠命令模式,所有评估逻辑均通过 modes/*.md 模块化实现。开发者可以通过配置 Google AI Studio 获取的 API Key 来驱动核心的 Gemini 模型能力,实现高效的文本分析与逻辑推理。

🎯 aiskill88 AI 点评 A 级 2026-05-16

创新的AI求职助手,集成多模态功能和可视化仪表板。高星数体现社区认可,Claude驱动保证质量。适合规模化应用。

📚 实用指南(长尾问题)
适合谁
  • 需要 career-ops 解决具体问题的开发者与运营人员
最佳实践
  • 先在测试环境跑通最小用例,再接入生产数据
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
部署方案
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
career-ops 中文教程career-ops 安装报错怎么办career-ops 与同类工具对比career-ops 最佳实践career-ops 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要 career-ops 解决具体问题的开发者与运营人员
⭐ 最佳实践
  • 先在测试环境跑通最小用例,再接入生产数据
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)

👥 适合人群

AI 技术爱好者研究人员和学生开发者和工程师技术创业者

🎯 使用场景

  • 本地部署运行,保护数据隐私,满足合规要求
  • 自定义集成到现有系统,扩展技术栈能力
  • 作为开源基础组件进行商业化二次开发

⚖️ 优点与不足

✅ 优点
  • +GitHub 44.3k Star,社区高度认可
  • +MIT 协议,可免费商用
  • +完全开源免费,无授权费用
  • +本地部署,数据完全自主可控
  • +开发者社区支持,遇问题可查可问
⚠️ 不足
  • 安装和初始配置可能需要一定技术基础
  • 功能完整性通常不如成熟商业产品
  • 技术支持主要依赖开源社区,响应速度不稳定
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

🔗 相关工具推荐

📚 相关教程推荐
📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

支持主流招聘平台集成,具体支持列表见文档
💡 AI Skill Hub 点评

总体来看,智能求职助手 是一款质量优秀的AI工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。

📚 深入学习 智能求职助手
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 career-ops
原始描述 开源AI工作流:AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard,。⭐44.3k · JavaScript
Topics AI智能体工作流自动化求职系统Claude职业发展
GitHub https://github.com/santifer/career-ops
License MIT
语言 JavaScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/santifer/career-ops 🌐 官方网站  https://career-ops.org

收录时间:2026-05-13 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。

📺 订阅 AI Skill Hub Daily Telegram 频道
每天 8 条精选 AI Skill、MCP、Agent 与自动化工具推送
加入频道 →