Automate tailored resumes and cover letters for each job, publish HTML resumes on GitHub Pages, convert to PDFs with Gotenberg, and store files in Google Drive.
The AI agent pulls your experience data from the input database and tailors resumes and cover letters for each job listing. It hosts the generated HTML resume on GitHub Pages and converts it to a PDF with Gotenberg. It saves the final PDFs to Google Drive and notifies you when the process completes.
Tailors documents end-to-end using your data and job context.
Ingests job listing data and candidate profile inputs.
Retrieves and assembles relevant experience from the n8n Data Table via RAG.
Generates a tailored resume HTML optimized for each listing.
Generates a tailored cover letter aligned with job requirements.
Publishes the HTML resume to GitHub Pages for online hosting.
Converts HTML to PDF with Gotenberg and stores PDFs in Google Drive.
Before → you face five real pains: manual customization for each listing, inconsistent formatting, scattered sources for candidate data, risk of missing job keywords, and juggling hosting, PDF conversion, and storage across tools. After → you get five clear outcomes: fully tailored resumes and letters per listing, consistent formats, centralized data flow from n8n to outputs, hosted HTML resumes on GitHub Pages with PDFs in Google Drive, and automated completion notifications.
A simple 3-step flow that non-technical users can follow.
Collect job listing details and pull candidate data from the n8n Data Table using RAG to create a personalize plan.
Generate a tailored resume HTML and a tailored cover letter using an LLM, ensuring alignment with listed requirements.
Publish HTML to GitHub Pages, convert to PDF with Gotenberg, and store PDFs in Google Drive; notify on completion.
A realistic scenario showing end-to-end operation.
A software engineer with five years of experience pasting a Software Engineer job listing into the Telegram bot. The AI agent pulls relevant career data from the n8n table, tailors a resume and cover letter, hosts the HTML resume on GitHub Pages, converts it to PDF with Gotenberg, and saves the PDF in Google Drive. The entire process completes in about 5–10 minutes, delivering ready-to-submit documents with job-specific keywords and formatting.
Roles that gain from automated personalization and delivery.
Needs role-specific tailoring and keywords; benefits from automated formatting and quick delivery.
Requires alignment of analytical skills and projects with listing requirements.
Must emphasize campaigns, metrics, and growth experience per role.
Must highlight projects and internships for entry roles with tailored content.
Translates prior experience to new domain with job-specific language.
Keeps client materials up-to-date and ready for proposals across listings.
Core tools used to assemble and deliver personalized outputs.
Hosts the generated HTML resumes for each job listing.
Converts HTML resumes to PDFs and stores them in Drive.
Manages the Data Table and triggers RAG-based personalization.
Generates tailored cover letters and assists with resume tailoring.
Stores final PDFs and provides easy access to documents.
Practical scenarios where this AI agent adds value.
Common questions about using the AI agent for resumes and cover letters.
You provide the job listing text and your candidate data in the n8n Data Table. The AI agent uses RAG to combine listing details with your experience. You can also paste descriptions into the Telegram bot for quick processing. Outputs include a tailored HTML resume, tailored cover letter, and a downloadable PDF. The workflow runs end-to-end with automated hosting and storage.
Data is handled within your configured automation environment. You control access to the n8n table, GitHub repository, and Google Drive. Outputs are stored in your Drive space, keeping sensitive information within your own accounts. You can audit data flows and adjust permissions as needed.
Yes. You can modify the HTML resume template and the cover letter template. An LLM can help refine sections, phrasing, and keywords. The HTML is hosted on GitHub Pages, so you can update templates and publish changes easily.
The end-to-end process typically completes within a few minutes, depending on the size of your data and the complexity of the job description. The system runs asynchronously, with a notification once everything is generated and stored. You can trigger runs for multiple job listings in sequence or in parallel if configured.
Yes. The agent can process multiple job listings by queuing tasks and generating per-listing resumes and letters. Each output is isolated and stored with job-specific references. You’ll have separate HTML previews and PDFs for each listing.
The agent produces a live HTML resume hosted on GitHub Pages and a downloadable PDF via Gotenberg. It also stores the PDF copies in Google Drive for easy access. You can reuse the HTML as a shareable resume link for online applications or profiles.
No coding knowledge is required. The workflow uses low-code tools (n8n) and an LLM for content creation, with hosting and storage handled automatically. You manage inputs, templates, and permissions, while the system handles personalization and delivery.
Automate tailored resumes and cover letters for each job, publish HTML resumes on GitHub Pages, convert to PDFs with Gotenberg, and store files in Google Drive.
