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Agent Skill · 研究检索

job-auto-apply(职位自动申请)

job-auto-apply 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

job-auto-apply 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,464。

总安装 388周安装 16GitHub Stars 1下载 127核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:job-auto-apply(职位自动申请)
来源仓库:https://github.com/liruihan000/claude-job-auto-apply
仓库路径:skills/job-auto-apply
安装命令:
npx skills add https://github.com/liruihan000/claude-job-auto-apply --skill job-auto-apply
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/liruihan000/claude-job-auto-apply --skill job-auto-apply

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

job-auto-apply 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定仓库安装并使用该技能。安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。

建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/job-auto-apply

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/liruihan000/claude-job-auto-apply --skill job-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

job-auto-apply 怎么安装?

在终端执行 npx skills add https://github.com/liruihan000/claude-job-auto-apply --skill job-auto-apply。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

job-auto-apply 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

job-auto-apply 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

job-auto-apply 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

job-auto-apply 用的人多吗?

公开数据是累计安装 388 次,近一周安装 16 次,下载 127 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

job-auto-apply 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
job-auto-apply

职位自动申请 · 本页

3881操作浏览器未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Job Auto-Apply

Configuration: On startup, run node ${CLAUDE_SKILL_DIR}/scripts/bootstrap.js to load all runtime parameters. All values below prefixed with config.* come from config.json. If bootstrap.js returns ready: false, read ${CLAUDE_SKILL_DIR}/SETUP.md and guide user through setup. Tools per Playwright instance: browser_snapshot, browser_navigate, browser_click, browser_type, browser_fill_form, browser_select_option, browser_file_upload, browser_press_key, browser_evaluate, browser_take_screenshot, browser_wait_for, browser_tabs, browser_hover

Stage -1: Auto-Check on Startup (MANDATORY)

Every time this skill is invoked:

  1. Check user intent:

- If the user asks a question or says "discuss"/"analyze"/"review"/"look at" about a job → enter Discussion Mode (see below). - If the user says "apply"/"submit"/"投" + a specific job URL or role → enter Single Apply Mode: run the Phase 1 research steps for that job (fetch JD, extract keywords, research company, create folder), then go directly to Phase 2 → Phase 2.5 → Phase 3 for that job only. - Otherwise → continue to auto-apply flow.

  1. Run node ${CLAUDE_SKILL_DIR}/scripts/bootstrap.js → load config + check readiness

- If ready: false → read ${CLAUDE_SKILL_DIR}/SETUP.md and guide user through missing items. Do NOT proceed to any Phase. Do NOT attempt workarounds or alternative tools. - Directories and TRACKER.md are auto-created by bootstrap.js

  1. Read applications/TRACKER.md
  2. Count Submitted column entries with today's date → today_submitted
  3. List ⬜ NOT SUBMITTED entries with materials ready
  4. Report: "Today: X/{config.daily_target} submitted, Y pending"
  5. If today_submitted >= config.daily_target → report done and stop
  6. Otherwise → enter Auto-Apply Pipeline immediately

AUTONOMY: If config.automation.manual_review: false → full autonomy, never ask user, never stop mid-loop. If true → pause between phases for user review before proceeding.


Discussion Mode

When the user wants to discuss a specific job rather than auto-apply:

  1. Read the job posting (via WebFetch, Playwright, or user-provided text)
  2. Analyze: role requirements, tech stack, team, company info
  3. Compare against the user's resumes in uploaded-resumes/ and user-profile.md
  4. Discuss with the user: fit assessment, pros/cons, resume strategy, questions to ask
  5. Do NOT enter the Auto-Apply Pipeline. Stay in conversation until the user says to apply or ends the discussion.
  6. If the user says "apply" or "submit" → add to TRACKER.md and proceed to Phase 2 for this job only.

Auto-Apply Pipeline

Phase 1: Search + Research

Find jobs until pending + today_submitted >= config.daily_target.

Search config.search.platforms in parallel per ${CLAUDE_SKILL_DIR}/references/search-guide.md. Searches may use Playwright MCP, WebSearch, or WebFetch for job discovery. Filter per ${CLAUDE_SKILL_DIR}/references/selection-strategy.md. Deduplicate.

For each candidate job — complete ALL steps before moving to the next job:

  1. Fetch the full JD text (do not add to TRACKER yet)
  2. Apply ALL filters from ${CLAUDE_SKILL_DIR}/references/selection-strategy.md — especially sponsorship and citizenship checks. If the job fails any filter → skip entirely, do not create folder, do not add to TRACKER
  3. Only if the job passes all filters — complete ALL of the following before proceeding to the next job: a. Add a row to TRACKER.md as ⬜ NOT SUBMITTED b. Create folder applications/YYYY-MM-DD_Company_Role/ c. Save full JD text to {APP_FOLDER}/jd.md d. Extract JD keywords → {APP_FOLDER}/jd-keywords.json (format: {"required_skills":[], "preferred_skills":[], "keywords":[]}) e. Find and read the company About/Mission page; save summary to {APP_FOLDER}/notes.md (include: industry, product, size, stage, culture, JD URL) f. Write {APP_FOLDER}/STATUS.md as ⬜ NOT SUBMITTED A job is only "done" in Phase 1 when all 6 files exist: TRACKER row + folder + jd.md + jd-keywords.json + notes.md + STATUS.md. Partial completion = not done.

Review checkpoint (if config.automation.manual_review: true): Show the user the list of jobs found (company, role, platform, URL). Wait for user to confirm which jobs to proceed with. Remove any rejected jobs from TRACKER.md and their folders.

Phase 1.5: Network Scan (optional — requires LinkedIn login in Playwright profile)

For each company in TRACKER.md with ⬜ status:

  1. Navigate to LinkedIn: linkedin.com/search/results/people/?keywords={COMPANY}&network=%5B%22F%22%5D (filters to 1st-degree connections)
  2. If connections found at this company → add their name and title to the job's Notes column in TRACKER.md (e.g. "🤝 John Doe - SWE @ Company")
  3. Move jobs with connections to higher priority

Skip this phase if LinkedIn is not logged in or if it gets blocked. Do not spend more than 30 seconds per company.

Phase 2: Prepare (resume + cover letter only)

For each job whose STATUS.md contains ⬜ NOT SUBMITTED AND whose folder contains jd.md. All research is already done — read local files only, no web requests needed.

  1. Read {APP_FOLDER}/jd.md — full JD text
  2. Read {APP_FOLDER}/jd-keywords.json — extracted keywords
  3. Read {APP_FOLDER}/notes.md — company info
  4. Select template from uploaded-resumes/ per ${CLAUDE_SKILL_DIR}/references/template-guide.md
  5. Read user-profile.md for personal info (contact, work auth, EEO)
  6. Tailor resume per ${CLAUDE_SKILL_DIR}/references/tailoring-guide.md
  7. Generate cover letter per ${CLAUDE_SKILL_DIR}/references/cover-letter-guide.md (if config.prepare.cover_letter_required)
  8. Generate DOCX + PDF
  9. Write STATUS.md as 📁 PREPARED — NOT SUBMITTED

Can parallelize with subagents (no browser needed). Use the Prepare Subagent Prompt Template below.

After all Prepare subagents complete — sync TRACKER.md: Scan every applications/*/STATUS.md. For each folder with 📁 PREPARED or ✅ SUBMITTED, ensure the corresponding TRACKER.md row reflects that status.

Phase 2.5: Auto-Review (MANDATORY — always runs)

After all materials are prepared, the main agent reviews each application. Run these checks:

  1. Content: Apply the same rules from ${CLAUDE_SKILL_DIR}/references/tailoring-guide.md to verify compliance.
  2. Format: Read the generated PDF and check for rendering issues — stray markdown characters (*, **, #), broken formatting, garbled text, missing sections.
  3. Page fit: Verify exactly 1 page — not overflowing, not too short.
  4. AI writing detection + ATS keyword score: Run node ${CLAUDE_SKILL_DIR}/scripts/ats_score.js {APP_FOLDER}/resume.md {APP_FOLDER}/jd-keywords.json. (jd-keywords.json was already created in Phase 1 — do not regenerate it.) Check results:

- ats_score < 60 → add missing keywords naturally into resume, regenerate - ai_phrases_found → replace flagged phrases with suggested alternatives - ai_patterns_found → rewrite affected sentences

  1. ATS parse check: Run node ${CLAUDE_SKILL_DIR}/scripts/ats_parse_check.js {APP_FOLDER}/resume.pdf. Check results:

- status: FAIL → fix errors (missing sections, bad formatting), regenerate - status: WARN → review warnings, fix if possible

Auto-fix any issues found, regenerate DOCX + PDF if changed.

Review checkpoint (if config.automation.manual_review: true): After auto-review, show the user a summary of each prepared application and any issues found/fixed. Wait for user to confirm which to submit. Mark rejected ones as ❌ SKIPPED in TRACKER.md.

Phase 3: Submit

Two modes depending on config.automation.manual_review:

Manual Review Mode (manual_review: true) — Parallel subagents, user submits manually

Subagents still run in parallel across the N Playwright instances. Each subagent's job ends at the review page — the user submits manually in the browser.

Subagent behavior (manual_review: true):

1. Navigate to job URL (opens a new tab in the assigned Playwright browser instance)
2. Fill all forms and upload tailored resume as normal
3. Navigate to the final review/confirmation page — do NOT click Submit
4. Take screenshot → {APP_FOLDER}/review-screenshot.png
5. Return "REVIEW_READY: {COMPANY} — {ROLE} | screenshot: {APP_FOLDER}/review-screenshot.png"
   (Task is complete — browser tab stays open at the review page)

Main agent behavior (manual_review: true):

active_subagents = 0
WHILE today_submitted < config.daily_target OR active_subagents > 0:
    // Dispatch up to N subagents (N = config.submit.parallel_instances)
    WHILE active_subagents < N AND more jobs with 📁 PREPARED:
        Launch next subagent (run_in_background: true, mode=REVIEW_ONLY)
        active_subagents++

    // Handle incoming results (non-blocking — process as they arrive)
    When a subagent returns REVIEW_READY:
        active_subagents--
        Show user: "✋ {COMPANY} — {ROLE} ready. Screenshot: {APP_FOLDER}/review-screenshot.png
                    Submit in browser → reply 'submitted {COMPANY}' | 'skip {COMPANY}' | 'stop'"

    When user replies:
        "submitted {COMPANY}" → update TRACKER.md ✅, today_submitted++
        "skip {COMPANY}"      → update TRACKER.md ❌ SKIPPED
        "stop"                → drain active subagents then exit loop
END WHILE
Autonomous Mode (manual_review: false) — Parallel subagents
WHILE today_submitted < config.daily_target:
    1. Pick up to N jobs whose STATUS.md contains `📁 PREPARED` (N = config.submit.parallel_instances)
    2. Launch N subagents (run_in_background: true), each assigned a unique Playwright prefix
    3. Wait for ALL subagents in this batch to complete
    4. For EACH completed subagent — immediately update TRACKER.md:
       SUCCESS → change Status to ✅ SUBMITTED, fill Submitted date column, today_submitted++
       FAILED  → change Status to ❌ SKIPPED, add reason to Notes column
       Do NOT batch these updates — update one row at a time as each result comes in.
    5. After updating TRACKER.md, verify the row was written correctly by re-reading it.
    6. If more pending → repeat. If none → back to Phase 1.
END WHILE

TRACKER.md update rule: The main agent owns TRACKER.md. Update immediately after each result — never batch or skip.

Phase 4: Retrospective (after daily target met or session end)

Check subagent return messages for FRICTION: lines:

  1. New ATS + friction → create ${CLAUDE_SKILL_DIR}/ats-handlers/{platform}.md with the workaround
  2. Known ATS + friction → append fix as one bullet to existing handler
  3. No friction lines → skip, no update needed

Prepare Subagent Prompt Template

Replace {variables}, pass to Agent tool:

Prepare application materials for {COMPANY} — {ROLE}.

**Application folder**: {APP_FOLDER}

Start from the research already saved in {APP_FOLDER}. You may do additional web research if needed (e.g. deeper company info, product details for cover letter).

**Input files (already exist in {APP_FOLDER}):**
- `jd.md` — full job description text
- `jd-keywords.json` — extracted JD keywords
- `notes.md` — company info (industry, product, size, culture)

**Steps:**
1. Read `{APP_FOLDER}/jd.md`, `{APP_FOLDER}/jd-keywords.json`, `{APP_FOLDER}/notes.md`
   **JD completeness check**: If `jd.md` is missing, empty, or clearly truncated (< 300 words, no responsibilities/requirements section), re-fetch the full JD from the URL in `notes.md` and overwrite `jd.md` and `jd-keywords.json`.
2. Select the best matching template from `uploaded-resumes/` per `${CLAUDE_SKILL_DIR}/references/template-guide.md` — read its full content for experience/skills
3. Read `user-profile.md` for personal info (contact, work auth, EEO)
4. Tailor resume per `${CLAUDE_SKILL_DIR}/references/tailoring-guide.md`
   **Format**: follow `${CLAUDE_SKILL_DIR}/references/resume-format-spec.md` exactly. `create_resume.js` enforces this automatically.
5. Write `resume-config.json` (structured data for DOCX generation)
6. Generate DOCX: `node ${CLAUDE_SKILL_DIR}/scripts/create_resume.js {APP_FOLDER}/resume-config.json {APP_FOLDER}/resume.docx`
7. Generate PDF: `libreoffice --headless --convert-to pdf --outdir {APP_FOLDER} {APP_FOLDER}/resume.docx`
8. **Page check**: Read the generated PDF and verify exactly 1 page. If not, reduce bullets per role (min 1) and regenerate. Repeat until exactly 1 full page.
9. If `config.prepare.cover_letter_required`: write `cover-letter-config.json`, generate cover_letter.docx + PDF — reference specific company details from notes.md
10. Write `STATUS.md` as `📁 PREPARED — NOT SUBMITTED`
11. Do NOT submit anything — only prepare materials
12. Do NOT fabricate experience — only use info from the resume template
13. Return "PREPARED: {COMPANY} — {ROLE}" when done

Submit Subagent Prompt Template

Replace {variables}, pass to Agent tool:

Submit application to {COMPANY} — {ROLE}.

**Mode:** {SUBMIT_MODE}  (either "AUTO_SUBMIT" or "REVIEW_ONLY")

**Goal:**
- AUTO_SUBMIT: Fill all forms, upload resume, and click Submit.
- REVIEW_ONLY: Fill all forms, upload resume, navigate to review/confirmation page — do NOT click Submit. Take screenshot and return "REVIEW_READY".

**Tools:** ONLY use `{PLAYWRIGHT_PREFIX}*` tools. Never use other playwright instances.

**Data sources:**
- `user-profile.md` — personal info, contact, work auth, EEO defaults
- `secrets.md` — credentials for login/registration
- Resume: {RESUME_PATH}
- Cover letter: {COVER_LETTER_PATH} (if exists)
- Additional documents: {ADDITIONAL_DOCS}
- ATS strategies: `${CLAUDE_SKILL_DIR}/ats-handlers/` (read matching platform file if recognized)

**Approach:** Observe the page at each step, decide what to do next. Every ATS is different — adapt to what you see rather than following a fixed sequence. General flow: navigate → find apply button → fill forms → upload files → review → submit. But let the page guide you.

**Constraints:**
- Auto-agree all terms/cookies/eSignatures (if config.automation.auto_agree_terms)
- Auto-register accounts if needed (if config.automation.auto_register_accounts)
- Fill ALL required fields — never leave a field empty or on "Select..."
- **Resume upload**: ALWAYS upload {RESUME_PATH} — never use a previously saved resume from the ATS profile, even if one is already shown. Actively replace it.
- Screening questions: authorized=Yes, sponsorship=Yes (+explanation), 18+=Yes, background=Yes, previously worked=No. Check for follow-up fields after each answer.
- Experience/Education dates must match the tailored resume exactly — never guess
- Before submitting: verify all required fields are filled
- Screenshot before submit → {APP_FOLDER}/review-screenshot.png (if config.submit.screenshot_review)
- Screenshot after submit → {APP_FOLDER}/confirmation-screenshot.png (if config.submit.screenshot_confirmation)
- If stuck on any interaction for >config.submit.max_retries_per_form retries, skip and report why

**Output:**
- AUTO_SUBMIT: Write {APP_FOLDER}/STATUS.md as ✅ SUBMITTED. Return "SUCCESS" or "FAILED: [reason]"
- REVIEW_ONLY: Take screenshot → {APP_FOLDER}/review-screenshot.png. Do NOT write STATUS.md. Return "REVIEW_READY: {COMPANY} — {ROLE}"
- If friction encountered, append: "FRICTION: [what happened] → [what worked]"

References

  • Job search: ${CLAUDE_SKILL_DIR}/references/search-guide.md — platform methods, deduplication
  • Job selection: ${CLAUDE_SKILL_DIR}/references/selection-strategy.md — filters, prioritization
  • Resume tailoring: ${CLAUDE_SKILL_DIR}/references/tailoring-guide.md — 8-step checklist
  • Resume format: ${CLAUDE_SKILL_DIR}/references/resume-format-spec.md — Times New Roman, black headers, 2-line company format, bullet skills
  • Cover letter: ${CLAUDE_SKILL_DIR}/references/cover-letter-guide.md — structure, rules
  • Template selection: ${CLAUDE_SKILL_DIR}/references/template-guide.md — which template for which JD
  • Filing & tracking: ${CLAUDE_SKILL_DIR}/references/filing-guide.md — folder structure, TRACKER format
  • User profile: user-profile.md — personal info, contact, work auth, EEO
  • Credentials: secrets.md — ATS login, registration, Google Sign-In

Key Rules

  • Browser tool rules:

- Job searching: WebSearch, WebFetch, and Playwright are all OK. - Everything that interacts with a web page (form-filling, clicking, uploading, submitting, logging in, registering): **Playwright MCP (mcp__playwright*) ONLY. Never use BrowserMCP, Claude-in-Chrome, or other browser tools. - If Playwright is unavailable, STOP and run SETUP** — do not attempt alternative browser tools.

  • Tailor every resume. Never submit a template as-is.
  • Never fabricate experience — only use info from the resume templates in uploaded-resumes/.
  • Pre-submit validation — JS check all required fields before clicking submit.
  • On error: retry up to config.submit.max_retries_per_form times, then skip and log reason.
  • Never stop until daily target is met.
  • Match user's language (see config.preferences.response_language).
  • Self-updating: When user requests a new search platform, ATS handler, or config change, update the corresponding files immediately (config.json, ${CLAUDE_SKILL_DIR}/references/search-guide.md, ${CLAUDE_SKILL_DIR}/ats-handlers/*.md) — don't ask user to edit manually.

平台分布

Codex

34.56%
按下载量换算44

Claude

30.39%
按下载量换算39

Cursor

19.94%
按下载量换算25

Gemini CLI

9.58%
按下载量换算12

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

未通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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