Install
openclaw skills install resumexManage 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.
openclaw skills install resumexYou are connected to Resumex (https://resumex.dev) — a resume management platform with a REST API. You have two core capabilities:
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.
Before doing anything on the user's behalf, be transparent about these points if they ask:
resumex.dev/api/v1/* (resume data) and — only when requested — api.telegram.org (Telegram delivery). No other outbound calls are made.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.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.AUTO_APPLY_MODE defaults to false. Always display the job list and wait for user selection before applying.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.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.
rx_... keyRESUMEX_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
On first use of auto-apply, run these commands. Recommend the user installs in a virtualenv for isolation:
# Recommended: use a virtual environment
python3 -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
# Install dependencies (~10MB package + ~300MB Chromium browser binary)
pip3 install -r {baseDir}/requirements.txt
python3 -m playwright install chromium
If pip3 is not found, try pip instead.
⚠️ 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-stealthis 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).
| Say... | What happens |
|---|---|
| "Find me jobs" | Full flow: onboarding → search → approve → apply → track |
| "Search for [role] jobs in [location]" | Search only — show list, no applying |
| "Apply to jobs for me" | Use saved preferences, skip setup if done |
| "Set my job search preferences" | Re-run the onboarding questions |
| "Show my job applications" | List jobs logged in Resumex Job Tracker |
| Say... | Effect |
|---|---|
| "Show my resume" | Full resume summary |
| "Update my phone to +91 98765 43210" | Edit profile field |
| "Add a job: SWE at Google, Jan 2024–Present" | Add experience |
| "Remove my internship at XYZ" | Delete experience (confirm first) |
| "Add Python, Docker to my skills" | Add skills |
| "Tailor my resume for: [paste JD]" | AI rewrite for job description |
| "Send me my resume on Telegram" | Send formatted summary via Telegram |
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").
Fetch the user's live resume data:
curl -s -X GET https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY"
Parse:
workspace = response.data
activeResume = workspace.resumes.find(r => r.id === workspace.activeResumeId)
resumeData = activeResume.data
Extract these fields for job matching:
resumeData.profile → fullName, email, phone, location, linkedin, website, summaryresumeData.skills[] → flatten all skill namesresumeData.experience[] → recent roles and companiesresumeData.education[] → degrees and institutionsUSE YOUR BUILT-IN WEB SEARCH to find job listings. Do NOT rely on external scripts for search.
Construct targeted search queries based on user preferences + resume:
"[role]" "[location]" site:linkedin.com/jobs
"[role]" "[location]" site:indeed.com
"[role]" "[location]" site:greenhouse.io
"[role]" "[location]" site:lever.co
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:
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
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:
"1,3" → apply to those jobs"all" → apply to all listed jobs"none" or "skip" → don't apply, end sessionIf 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.
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.
For each approved job, run the Playwright helper:
python3 {baseDir}/job_applier.py \
--url "[JOB_URL]" \
--name "[resumeData.profile.fullName]" \
--email "[resumeData.profile.email]" \
--phone "[resumeData.profile.phone]" \
--location "[resumeData.profile.location]" \
--linkedin "[resumeData.profile.linkedin]" \
--website "[resumeData.profile.website]" \
--summary "[resumeData.profile.summary first 300 chars]" \
--headless "$HEADLESS_BROWSER"
The script will return a JSON result on stdout:
{
"status": "applied" | "manual_required" | "failed",
"notes": "...",
"filled_url": "https://..."
}
Handle each result:
"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.
After every application attempt (success OR manual), log to the Resumex Job Tracker:
curl -s -X POST https://resumex.dev/api/v1/jobs \
-H "Authorization: Bearer $RESUMEX_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"job": {
"id": "job-[unix_timestamp_ms]",
"company": "[company]",
"role": "[title]",
"status": "Applied",
"dateApplied": "[YYYY-MM-DD]",
"location": "[location]",
"link": "[url]",
"notes": "[result notes]",
"priority": "Medium",
"source": "[portal name]",
"lastUpdated": "[ISO timestamp]"
}
}'
Confirm: "📊 Logged to your Job Tracker. View at https://resumex.dev/app → Job Tracker tab."
After processing all approved jobs, show a summary table:
═══════════════════════════════════════════════════
🎉 Application Summary
═══════════════════════════════════════════════════
✅ Applied automatically: [N]
📎 Manual action needed: [N]
❌ Failed: [N]
✅ Software Engineer @ Google — Applied
📎 SWE II @ Flipkart — PDF required → [link]
❌ Backend Dev @ XYZ — Browser error
📊 All logged to Resumex Job Tracker.
View: https://resumex.dev/app → Job Tracker tab
All API calls go to https://resumex.dev/api/v1/agent with header Authorization: Bearer $RESUMEX_API_KEY.
resumex_get — Fetch resumecurl -s -X GET https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY"
Parse: workspace.resumes.find(r => r.id === workspace.activeResumeId).data
resumeData contains: profile, experience[], education[], skills[], projects[], achievements[]
resumex_update_profile — Edit profile fieldsEditable: fullName, email, phone, location, website, linkedin, github, summary
curl -s -X PATCH https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY" \
-H "Content-Type: application/json" \
-d '{"patch": {"profile": {"phone": "+91 98765 43210"}}}'
Confirm: ✅ Phone updated to +91 98765 43210.
resumex_add_experience — Add work experience{
"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"
}
resumeData.experience[] → POST full workspace:curl -s -X POST https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY" \
-H "Content-Type: application/json" \
-d '{"workspace": <FULL_WORKSPACE_JSON>}'
resumex_edit_experience — Edit an experience entryresumex_delete_experience — Remove an experience entryresumeData.experience[]. POST full workspace.✅ Removed [Role] at [Company].resumex_add_education — Add educationBuild:
{
"id": "edu-[unix_timestamp_ms]",
"institution": "Savitribai Phule Pune University",
"degree": "B.Tech Computer Science",
"startDate": "2019",
"endDate": "2023",
"score": "8.5",
"scoreType": "CGPA"
}
Fetch workspace → prepend → POST full workspace.
resumex_edit_education / resumex_delete_educationSame pattern as experience — find by institution/degree, modify, POST full workspace.
resumex_add_skill — Add skills"Skills".resumeData.skills[] (each: {id, category, skills: string[]}).{id: "sk-[timestamp]", category, skills}.curl -s -X PATCH https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY" \
-H "Content-Type: application/json" \
-d '{"patch": {"skills": <UPDATED_SKILLS_ARRAY>}}'
resumex_delete_skill — Remove skill or categoryFetch → 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_projectFind 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 descriptionresumex_get.profile.summary — 2–3 sentences aligned to JD keywords, active voiceexperience bullets — surface JD keywords, do NOT fabricate factscurl -s -X PATCH https://resumex.dev/api/v1/agent \
-H "Authorization: Bearer $RESUMEX_API_KEY" \
-H "Content-Type: application/json" \
-d '{"patch": {"profile": {"summary": "<rewritten>"}, "experience": [<rewritten array>]}}'
resumex_send_telegram — Send resume to TelegramRun:
python3 {baseDir}/send_pdf.py \
--api-key "$RESUMEX_API_KEY" \
--chat-id "$TELEGRAM_CHAT_ID" \
--bot-token "$TELEGRAM_BOT_TOKEN"
If TELEGRAM_BOT_TOKEN or TELEGRAM_CHAT_ID are not set, print the formatted resume to the chat and say:
"Here's your resume summary. To get the PDF: open https://resumex.dev/app → Download PDF, or open your portfolio → Ctrl+P → Save as PDF."
GET /api/v1/agent before any search/apply session.AUTO_APPLY_MODE=true is set./api/v1/jobs after every application attempt (success or manual)."company": "Google".| Error | Cause | Fix |
|---|---|---|
401 Invalid API Key | Key wrong or revoked | Dashboard → Resumex API → Regenerate Key |
404 No resume found | No active resume | Open resumex.dev/app and save your profile first |
HTTP 500 + SQL hint | Admin setup incomplete | Run api_keys_setup.sql in Supabase |
| Playwright not found | Not installed | Run: pip3 install -r {baseDir}/requirements.txt && python3 -m playwright install chromium |
| No jobs found | Search returned nothing | Try broader role/location, or search portals directly |
| Job Tracker POST fails | Non-fatal | Warn user, continue — offer to retry tracker POST separately |
RESUMEX_API_KEY is scoped to your account onlyTELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID live in your OpenClaw environment — Resumex never sees them