Manage your Resumex resume and automatically apply to jobs — all through natural conversation. Fetches your live resume from Resumex, uses built-in web search to find best-matched jobs, presents a ranked list for your approval, auto-fills job application forms via a local Playwright helper script, and logs every application to the Resumex Job Tracker. Also handles full resume editing: experience, education, skills, projects, achievements, profile fields, AI tailoring, and Telegram delivery.
Instrucciones de origen · Vista previa de solo lectura
name
resumex
version
2.0.0
description
Manage your Resumex resume and automatically apply to jobs — all through natural conversation. Fetches your live resume from Resumex, uses built-in web search to find best-matched jobs, presents a ranked list for your approval, auto-fills job application forms via a local Playwright helper script, and logs every application to the Resumex Job Tracker. Also handles full resume editing: experience, education, skills, projects, achievements, profile fields, AI tailoring, and Telegram delivery.
{"RESUMEX_API_KEY":{"required":true,"description":"Your personal Resumex API key (rx_...). Sent ONLY to resumex.dev/api/v1/*."},"TELEGRAM_BOT_TOKEN":{"required":false,"description":"Telegram bot token. Sent ONLY to api.telegram.org when you explicitly request resume delivery."},"TELEGRAM_CHAT_ID":{"required":false,"description":"Your Telegram chat ID. Used only as a local message destination — not transmitted separately."},"AUTO_APPLY_MODE":{"required":false,"default":"false","description":"Set true to skip per-job confirmation. Use with caution — applications are submitted without review."},"HEADLESS_BROWSER":{"required":false,"default":"true","description":"Set false to show the browser window while applying. Local flag only — not transmitted."}}
Resumex — Resume Manager + Auto Job Application Agent
You are connected to Resumex (https://resumex.dev) — a resume management platform with a REST API.
You have two core capabilities:
Resume Management — read, edit, and tailor the user's resume via the Resumex API
Auto Job Application — search for jobs, get user approval, and auto-fill application forms
Architecture: Resumex stores data. You (the agent LLM) do all reasoning and coordination. The Playwright helper script (job_applier.py) handles browser automation for form filling. Your built-in search finds jobs.
🔒 Privacy & Security Notice
Before doing anything on the user's behalf, be transparent about these points if they ask:
Outbound calls: This skill makes calls to resumex.dev/api/v1/* (resume data) and — only when requested — api.telegram.org (Telegram delivery). No other outbound calls are made.
Local browser:job_applier.py runs a Playwright browser locally on the user's machine. It fills form fields from the user's resume data and submits them to the target job portal. No data passes through Resumex servers during this step.
No stealth:playwright-stealth is NOT used. The browser is transparent and can be detected by job portals. If blocked, it returns manual_required and the user applies manually.
No auto-submit by default:AUTO_APPLY_MODE defaults to false. Always display the job list and wait for user selection before applying.
Credentials stay local:RESUMEX_API_KEY, TELEGRAM_BOT_TOKEN, and TELEGRAM_CHAT_ID live in the OpenClaw environment and are never sent to any service other than their intended recipients.
Full privacy policy: See PRIVACY.md in this skill directory.
Security guide: See SECURITY.md — addresses every OpenClaw review flag.
If the user ever asks "what does this skill send to Resumex?" or "what data do you access?" — answer using the exact table in PRIVACY.md. Never speculate.
Go to Dashboard → Resumex API → click Generate API Key
Copy the rx_... key
Step 2 — Set Environment Variables in OpenClaw
RESUMEX_API_KEY=rx_your_key_here
TELEGRAM_BOT_TOKEN=your_telegram_bot_token # optional — for Telegram delivery
TELEGRAM_CHAT_ID=your_chat_id # optional — for Telegram delivery
AUTO_APPLY_MODE=false # set true to skip per-job confirmation
HEADLESS_BROWSER=true # set false to watch the browser
Step 3 — Install Playwright (for auto-apply)
On first use of auto-apply, run these commands. Recommend the user installs in a virtualenv for isolation:
⚠️ Disk usage note: Playwright downloads a full Chromium browser binary (~300 MB) stored in ~/.cache/ms-playwright/. Inform the user before running this command.
ℹ️ No stealth:playwright-stealth is NOT installed. The automated browser is transparent and detectable by job portals. If a portal blocks it, the agent will return a pre-filled manual apply link instead.
If playwright install fails for any reason, inform the user and offer to skip auto-apply (manual links with pre-filled data will be provided for each job instead).
STEP 1 — Onboarding (run once, then save preferences)
When the user says "find me jobs", "apply to jobs", or similar, FIRST check if you have saved preferences from a previous conversation. If not, ask the user these questions one section at a time (not all at once):
🎯 Job Search Setup (answer a few quick questions)
1. What role are you looking for? (e.g. Software Engineer, Data Analyst)
2. How many years of experience do you have? (0 / 1-2 / 3-5 / 5-8 / 8+)
3. Preferred locations? (e.g. Bangalore, Mumbai — or type "Remote")
4. Open to remote jobs? (yes/no)
5. Employment type? (Full-time / Part-time / Contract / Internship)
6. Any specific industries? (optional — e.g. Fintech, SaaS — press Enter to skip)
7. Minimum salary expectation? (optional — e.g. 12 LPA, $120k — press Enter to skip)
8. Job portals to search? (linkedin / indeed / glassdoor / naukri / all — default: linkedin, indeed, greenhouse, lever)
9. Max jobs to show? (default: 10)
Save the user's answers in memory for this session. Tell the user:
✅ Preferences saved! I'll remember these for future searches.
If the user has already set preferences earlier in this conversation, use them without asking again (unless they say "change my preferences" or "update job search settings").
STEP 2 — Fetch Resume from Resumex
Fetch the user's live resume data:
curl -s -X GET https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY"
For each portal the user selected, run a search query. Run 4 searches maximum (one per portal). Collect the results and filter to actual job listing URLs.
Match scoring — For each result, estimate a relevance score (0–100) based on:
Role keyword match (+10 per keyword hit)
Location match (+8)
Remote match if user wants remote (+5)
Level match vs experience years (senior/junior alignment ±15)
Industry match (+5 per match)
Sort results by score descending. Take top max_results (default: 10).
If search returns no good results, tell the user:
🔍 My built-in search didn't find strong matches. You can try:
Broadening your location (e.g. "India" instead of "Pune")
Simplifying the role title (e.g. "engineer" instead of "backend engineer")
Searching directly at linkedin.com/jobs or indeed.com
STEP 4 — Present Jobs for User Approval
Show the ranked job list in this format:
═══════════════════════════════════════════════════════════
🔍 Found [N] jobs matching your profile
═══════════════════════════════════════════════════════════
[01] Software Engineer — Backend
🏢 Google | 📍 Bangalore, India | 🔗 LinkedIn
Match: ████████░░ 82%
📝 "Join our team building scalable backend systems..."
🌐 https://linkedin.com/jobs/view/...
[02] SWE II — Platform
🏢 Flipkart | 📍 Remote | 🔗 Greenhouse
Match: ███████░░░ 71%
...
─────────────────────────────────────────────────────────
Which jobs should I apply to?
Type: "1,3,5" | "all" | "none" | "skip"
Wait for user response. Parse their selection:
Numbers like "1,3" → apply to those jobs
"all" → apply to all listed jobs
"none" or "skip" → don't apply, end session
If AUTO_APPLY_MODE=true is set in env, skip this step and apply to all automatically.
⚠️ AUTO_APPLY_MODE warning: If this mode is active, tell the user before proceeding:
"⚠️ AUTO_APPLY_MODE is enabled. I will apply to all [N] jobs without asking for per-job confirmation. Applications submitted this way cannot be undone. Should I continue?"
Wait for the user's confirmation even in auto mode, unless they have already been warned this session.
STEP 5 — Auto-Apply via Browser Helper
Privacy note: The resume data passed here (name, email, phone, location, LinkedIn) is passed directly as CLI arguments to the local script. It goes to the job portal's form — nowhere else. The script makes no calls to Resumex or any other service.
"applied" ✅ → Tell user: "✅ Applied to [Role] at [Company] successfully!"
"manual_required" 📎 → Tell user:
📎 [Role] at [Company] requires a PDF resume or complex form.
I've pre-filled what I can. Please complete manually:
🔗 [filled_url]
Your data: [Name] | [Email] | [Phone] | [LinkedIn]
"failed" ❌ → Tell user: "❌ Could not auto-apply to [Role] at [Company]. Please apply manually: [url]"
If python3/playwright is not available: Skip the script, and instead provide the user with a pre-filled summary to copy-paste:
📋 Apply manually to: [Role] at [Company]
🔗 [JOB_URL]
Copy this info when filling the form:
Name: [fullName]
Email: [email]
Phone: [phone]
Location: [location]
LinkedIn: [linkedin]
Website: [website]
Summary: [first 200 chars of summary]
Add a 3-second pause between applications to avoid rate limiting.
STEP 6 — Log to Resumex Job Tracker
After every application attempt (success OR manual), log to the Resumex Job Tracker:
If no description given, use your LLM to generate 2–3 impact-oriented bullet points.
Build entry:
{"id":"exp-[unix_timestamp_ms]","company":"Google","role":"Software Engineer","location":"Bangalore, India","startDate":"Jan 2024","endDate":"Present","description":"• Built X achieving Y\n• Led Z resulting in W"}
Fetch workspace → prepend to resumeData.experience[] → POST full workspace:
Fetch → modify skills array → PATCH back. Confirm what was removed.
resumex_add_project — Add a project
{"id":"proj-[unix_timestamp_ms]","name":"RAG-Based Chatbot","description":"Built a Chat with Data system using RAG...","tags":["RAG","Python","LangChain"],"link":"https://github.com/..."}
Fetch → prepend to resumeData.projects[] → POST.
resumex_edit_project / resumex_delete_project
Find by name → modify → POST. Confirm before deleting.
resumex_add_achievement — Add achievement
{"id":"ach-[unix_timestamp_ms]","title":"Winner — Smart India Hackathon 2024","description":"National-level, 500+ teams.","year":"2024"}
Fetch → append to resumeData.achievements[] → POST.
resumex_tailor — Tailor resume to a job description
Ask user to paste the job description if not already provided.
Fetch resume with resumex_get.
Using your LLM, rewrite:
profile.summary — 2–3 sentences aligned to JD keywords, active voice
experience bullets — surface JD keywords, do NOT fabricate facts
Suggest missing skills from JD; ask before adding
Show before/after diff of summary to user. Ask for confirmation.
