Resumex

Step 2 — Set environment variables in your OpenClaw agent:

RESUMEX_API_KEY=rx_your_key_here
TELEGRAM_BOT_TOKEN=your_telegram_bot_token     # optional — needed for Telegram delivery
TELEGRAM_CHAT_ID=your_chat_id                  # optional — your personal Telegram chat ID

Get your Telegram Bot Token: Message @BotFather → /newbot → copy the token. Get your Chat ID: Message @userinfobot on Telegram → it replies with your chat ID. API reference: resumex.dev/api-docs

💬 What You Can Say

Write naturally — no special syntax required:

Profile

Experience

Education

Skills

Projects

Achievements

Tailoring & Delivery

🔧 Tool Reference

All API calls go to https://resumex.dev/api/v1/agent with header Authorization: Bearer $RESUMEX_API_KEY.

Two safe update methods:

• PATCH {"patch": {...}} → updates only specified fields. Use for profile fields and skills. Always prefer PATCH over POST when possible.
• POST {"workspace": <full_json>} → replaces the entire workspace. Required when modifying arrays (experience, education, projects, achievements). Always fetch fresh data immediately before a POST.

resumex_get — Fetch resume

curl -s -X GET https://resumex.dev/api/v1/agent \
  -H "Authorization: Bearer $RESUMEX_API_KEY"

Parse the response:

workspace = response.data
activeResume = workspace.resumes.find(r => r.id === workspace.activeResumeId)
resumeData = activeResume.data

resumeData contains: profile, experience[], education[], skills[], projects[], achievements[]

Display to user as clean Markdown, grouped by section.

resumex_update_profile — Edit profile fields

Editable fields: fullName, email, phone, location, website, linkedin, github, summary

1. PATCH only the changed field(s) — never touch others:

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"}}}'

2. Confirm: ✅ Phone updated to +91 98765 43210.

resumex_rewrite_summary — AI-rewrite profile summary

1. Fetch resume with resumex_get.
2. Using your LLM, rewrite resumeData.profile.summary for the requested role/tone.
   • 2–3 sentences, active voice, role-specific keywords, no generic buzzwords.
3. Show the user the new summary and ask for confirmation before saving.
4. On confirmation, PATCH:

curl -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 summary>"}}}'

5. Confirm: ✅ Summary updated.

resumex_add_experience — Add work experience

1. Extract from user: company, role, location, startDate, endDate, description/bullets.
2. If no description given, use your LLM to generate 2–3 impact-oriented bullet points for the role.
3. Build the 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"
}

4. Fetch workspace. Prepend the new entry to resumeData.experience[].
5. POST the full modified workspace back:

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>}'

6. Confirm: ✅ Added Software Engineer at Google.

resumex_edit_experience — Edit an existing experience entry

1. Fetch workspace. Find the experience entry by company name or role (case-insensitive match).
2. If multiple matches, ask user to clarify which one.
3. Apply only the user's requested changes to that entry (e.g., fix dates, update bullets).
4. POST the full modified workspace back.
5. Confirm what changed: ✅ Updated end date for Google → Dec 2024.

resumex_delete_experience — Remove an experience entry

1. Fetch workspace. Find the entry by company/role name.
2. If multiple matches, ask user to clarify.
3. Show the entry to the user and ask for confirmation before deleting.
4. On confirmation, remove the entry from resumeData.experience[].
5. POST the full modified workspace back.
6. Confirm: ✅ Removed [Role] at [Company].

resumex_add_education — Add education

1. Extract: institution, degree, field, startDate, endDate, score, scoreType (CGPA or Percentage).
2. Build:

{
  "id": "edu-<unix_timestamp_ms>",
  "institution": "Savitribai Phule Pune University",
  "degree": "B.Tech Computer Science",
  "startDate": "2019",
  "endDate": "2023",
  "score": "8.5",
  "scoreType": "CGPA"
}

3. Fetch workspace. Prepend to resumeData.education[]. POST full workspace.
4. Confirm: ✅ Added B.Tech CS at SPPU.

resumex_edit_education — Edit an education entry

1. Fetch workspace. Find entry by institution or degree name.
2. Apply only the requested changes.
3. POST full modified workspace. Confirm what changed.

resumex_delete_education — Remove an education entry

1. Fetch workspace. Find entry. Show it to user and confirm before deleting.
2. Remove from resumeData.education[]. POST full workspace.
3. Confirm: ✅ Removed [Degree] from [Institution].

resumex_add_skill — Add skills

1. Extract skill names and optional category from user message. Default category: "Skills".
2. Fetch workspace. Check resumeData.skills[] (each item: {id, category, skills: string[]}).
3. If category exists (case-insensitive): merge new skills in, deduplicating.
4. If category does not exist: create { "id": "sk-<timestamp>", "category": "...", "skills": [...] } and append.
5. PATCH only the skills array:

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>}}'

6. Confirm: ✅ Added Python, Docker to Skills.

resumex_delete_skill — Remove a skill or skill category

1. Fetch workspace.
2. Remove single skill: Find the category containing the skill (case-insensitive). Remove the skill from the skills[] array. If the category becomes empty, remove the whole category object.
3. Remove category: Remove the entire category object from resumeData.skills[].
4. PATCH the updated skills array back.
5. Confirm: ✅ Removed Docker from Skills. or ✅ Deleted Frameworks category.

resumex_add_project — Add a project

1. Extract: name, description, tags/technologies, link (optional).
2. Build:

{
  "id": "proj-<unix_timestamp_ms>",
  "name": "RAG-Based Smart Attendance Chatbot",
  "description": "Built a Chat with your Data system using RAG to automate attendance queries, reducing admin time by 40%.",
  "tags": ["RAG", "NLP", "Python"],
  "link": "https://github.com/..."
}

3. Fetch workspace. Prepend to resumeData.projects[]. POST full workspace.
4. Confirm: ✅ Added project: RAG-Based Smart Attendance Chatbot.

resumex_edit_project — Edit a project

1. Fetch workspace. Find project by name (case-insensitive).
2. Apply only the user's requested changes. POST full workspace.
3. Confirm what changed.

resumex_delete_project — Remove a project

1. Fetch workspace. Find project by name. Show it and ask for confirmation.
2. Remove from resumeData.projects[]. POST full workspace.
3. Confirm: ✅ Removed project: [Name].

resumex_add_achievement — Add an achievement

1. Extract: title, description (optional), year (optional).
2. Build:

{
  "id": "ach-<unix_timestamp_ms>",
  "title": "Winner — Smart India Hackathon 2024",
  "description": "National-level hackathon with 500+ competing teams.",
  "year": "2024"
}

3. Fetch workspace. Append to resumeData.achievements[]. POST full workspace.
4. Confirm: ✅ Added achievement: Winner — Smart India Hackathon 2024.

resumex_delete_achievement — Remove an achievement

1. Fetch workspace. Find achievement by title. Show it and confirm before deleting.
2. Remove from resumeData.achievements[]. POST full workspace.
3. Confirm: ✅ Removed achievement: [Title].

resumex_tailor — Tailor resume to a job description

All AI reasoning happens in your agent. Resumex only stores the final result.

1. If the user hasn't pasted a JD, ask: "Please paste the job description you'd like to tailor for."
2. Fetch resume with resumex_get.
3. Using your LLM (not Resumex), do:
   • Rewrite summary: 2–3 sentences aligned to the JD's key stack/domain. Active voice, no filler phrases.
   • Rewrite experience bullets: Surface JD keywords and impact phrases. Do not fabricate or add facts — only re-emphasize what's already there.
   • Review skills: Identify skills mentioned in the JD that the user doesn't have listed. Surface them as suggestions and ask before adding.
4. Show a before/after diff of the summary to the user. Ask if they want to review full experience changes too.
5. On confirmation, PATCH:

curl -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 experience array>]
    }
  }'

6. Confirm: ✅ Resume tailored for [Job Title] at [Company].

resumex_send_telegram — Send resume to Telegram

1. Fetch resume with resumex_get.
2. Format a clean resume summary message (see send_pdf.py for formatter logic).
3. Run the helper script:

python3 {baseDir}/send_pdf.py \
  --api-key "$RESUMEX_API_KEY" \
  --chat-id "$TELEGRAM_CHAT_ID" \
  --bot-token "$TELEGRAM_BOT_TOKEN"

4. If TELEGRAM_BOT_TOKEN or TELEGRAM_CHAT_ID are not set, print the formatted resume to stdout and tell the user:

   "Here's your resume summary. To get the full PDF, open resumex.dev/app → click Download PDF or press Ctrl+P → Save as PDF."

Note: Resumex does not generate PDFs server-side. The PDF workflow is: Resumex data → your agent → Telegram message + portfolio link → user opens link → Ctrl+P → PDF

⚠️ Important Rules for the Agent

1. Always fetch fresh data immediately before any POST. Never reuse a workspace fetched earlier in the conversation — the user may have made changes via the web app in between.
2. Prefer PATCH over POST for profile fields and skills. Only use POST (full workspace) when modifying arrays.
3. Always confirm before deleting anything. Show the item to be deleted and require explicit user confirmation.
4. Never fabricate data. When tailoring, only rephrase what already exists.
5. Match entries by fuzzy name when the user refers to a company/role — e.g. "my Google job" should match "company": "Google".
6. When multiple entries match, list them and ask the user to clarify before proceeding.

🛡️ Error Handling

🔒 Security

• RESUMEX_API_KEY is scoped to your account only.
• TELEGRAM_BOT_TOKEN lives in your OpenClaw environment — Resumex never sees it.
• TELEGRAM_CHAT_ID lives in your OpenClaw environment — Resumex never sees it.
• All AI work runs locally in your agent. Resumex only stores what you explicitly send.
• Revoke agent access anytime: Dashboard → Resumex API → Revoke Key.
• Edits appear live at resumex.dev immediately after saving.