Boss Job Agent — Development skill for Claude Code
BOSS 直聘自动投递 skill:爬取 → 匹配 → 人工确认 → 投递,支持按行政区/商圈收窄(Claude Code skill).
How to install Boss Job Agent
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open zhangjinkang-zjk/boss-job-agent and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Boss Job Agent does
BOSS 直聘自动投递 skill:爬取 → 匹配 → 人工确认 → 投递,支持按行政区/商圈收窄(Claude Code skill).
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README
BOSS 直聘自动投递助手
一个跑在 [Claude Code](https://claude.ai/code) 里的求职自动化 skill:**爬取岗位 → 解析简历 → LLM 智能匹配 → 人工确认 → 自动投递**。
本项目**基于 [`zhansan379/boss-crawler-skill`](https://github.com/zhansan379/boss-crawler-skill)(MIT)做的定制 fork**,核心的九阶段流水线、简历解析、匹配引擎、投递模块全部来自上游。本仓库的主要增量是**按行政区/商圈收窄岗位池**。
安装
git clone https://github.com/zhangjinkang-zjk/boss-job-agent.git ~/.claude/skills/boss-job-agent
cd ~/.claude/skills/boss-job-agent
uv venv .venv --python 3.12
# Windows
uv pip install --python .venv/Scripts/python.exe -r requirements.txt
# macOS / Linux
uv pip install --python .venv/bin/python -r requirements.txt
Windows 下的 skill 目录在 `%USERPROFILE%\.claude\skills\boss-job-agent`。
装好后在 Claude Code 里输入 `/boss-job-agent` 即可启动。
**与本机已有的 `boss-crawler` 二选一。** 两者是同一套代码的不同版本,同时安装会出现两个功能重叠的 skill。
首次配置
1. LLM 配置
cp assets/llm_config.example.json assets/llm_config.json
填入你的 `base_url` / `model` / `api_key`。**`json_mode` 必须设为 `false`**(原因见下文「使用注意」)。
2. 招呼语
mkdir -p .local
cp config/greeting.example.txt .local/greeting.txt
改成你自己的版本。`.local/` 整个目录不进仓库。
3. 简历
- 图片简历:把多页 PNG 放进
.local/,用tools/merge_resume_png.py合并成一张长图(每个岗位只发一张附件) - YAML 简历:用
tools/yaml2md.py转成 Markdown,比 PDF 少排版噪音,解析更准
4. 首次登录
./tools/run.sh scripts/stages/boss_post_interactive.py --ensure-login
扫码登录,登录态会持久化到 `assets/chrome_user_data/`(不进仓库)。
用法
所有脚本**一律通过 `./tools/run.sh` 调用**,不要直接 `python scripts/...`。原因见「设计取舍」。
# 1. 爬取(城市级)
./tools/run.sh scripts/stages/boss_post_interactive.py -m custom \
-p "AI应用开发,Python后端" -c 合肥 -n 40 -d -y --run-dir
# 2. 写入区域白名单(本 fork 新增)
./tools/run.sh scripts/stages/infer_params.py \
--city 合肥 --keywords "AI应用开发,Python后端" --area "蜀山区,高新区"
# 3. 匹配(池子小就全量送模型)
./tools/run.sh scripts/pipeline.py --run-dir --from match \
--match-mode deep --top-n 60
# 4. 投递演练(不碰浏览器,只列名单)—— 必做
./tools/run.sh scripts/deliver/apply.py \
--
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