A new workflow template on n8n.io shows how a PDF resume can be turned into a structured, reusable database inside a Google Sheet in a matter of minutes. The template, titled Create a master CV Google Sheet from uploaded CVs with easybits, lets a user upload a CV through a web form. The workflow then sorts the work history, education, skills and contact details into separate tabs. It relies on the easybits Extractor, a community node for n8n, the open workflow automation platform.
What the template does
According to the description published on n8n.io, the goal is to give job seekers a single, clean record of their career. Instead of retyping details each time they apply for a role, users keep one master file that can feed other processes. The template positions this file as a foundation for tasks such as tailoring a CV to a specific job, tracking applications, and running a skills gap analysis.
The core idea is simple. Every experience entry, education record, skill and contact detail is extracted from the document and placed in the correct spreadsheet tab. The result is a structured dataset rather than a static file that has to be edited by hand.
How the pipeline works
n8n.io breaks the process into five stages. Each stage is a node or group of nodes in the workflow:
- Upload: the user drops a CV PDF into an n8n web form.
- Extract: the easybits Extractor pulls structured data such as experiences, education, skills and a summary from the document.
- Fan out: a Code node splits the extracted response into rows for each sheet tab.
- Append: four parallel branches write data to the four tabs of the Master CV sheet.
- Done: a completion screen confirms what has been imported.
The parallel design means the workflow writes to the sheet across all four tabs at once rather than one after another. For a user, the practical effect is that the wait ends with a populated spreadsheet and a confirmation screen.
Setting up the sheet and the extractor
Preparing the Google Sheet
The setup guide asks users to create a Google Sheet named Master CV with four tabs. Each tab has a defined set of column headers. The Master CV tab holds role, company, dates, bullets and skills. The Education tab holds degree, institution, dates and details. The Summary tab holds full name, email, LinkedIn URL, location, summary, languages and links. The fourth tab handles skills. The headers must stay in place, and the rest of each tab should be left empty, because the workflow fills the sheet automatically.
Connecting the extractor
The easybits Extractor is listed by n8n.io as a verified community node. On n8n Cloud it is available by default. Self-hosted users need to install it through the Community Nodes section of their settings, using the package name @easybits/n8n-nodes-extractor.
The extraction step is driven by ten fields. Each field has a plain-language description that tells the extractor what to look for. Examples include the full name as it appears at the top of the CV, a summary returned as written rather than paraphrased, and a list of work experiences in CV order with bullets kept in their original wording. Fields return null when the information is missing, and the skills field is designed to collect technical tools, frameworks, methodologies and certifications while leaving out soft skills such as communication.
n8n.io notes that the ten-field limit matches the free plan of easybits. That detail matters for readers who want to test the workflow without paying for a higher tier, since the template is designed to run as provided.
Why a master CV matters
Many professionals keep several versions of their CV, each tailored to a different role. Over time these files drift apart. A detail updated in one version may be missing from another, and reconciling them takes effort. A single structured source of truth reduces that problem. It also makes it easier to reuse information in other tools, whether for generating a targeted CV, logging applications, or comparing listed skills against the requirements of a job posting.
Spreadsheets are a practical choice for this purpose. Google Sheets is widely used, easy to share, and simple to query or connect to other applications. Storing career data in rows and columns also means it can be filtered, sorted and analysed without specialised software.
Limits and what to check
The template is not a perfect parser, and n8n.io is candid about that. The guide advises users to review all four tabs after the first import. Minor cleanup is normal, particularly for CVs with two-column or designer layouts, where text can be read out of order. Users should also check dates, job titles and skill names, since automated extraction can misread unusual formatting.
The workflow also includes a technical note. The easybits Extractor wraps its output in a data object, so the Code node reads from that location. A helper function is included to handle cases where list fields arrive as encoded text rather than arrays. According to the template description, this makes the workflow more robust across different response formats.
Users who want to adapt the template should keep these points in mind. Changing the column headers in the sheet without updating the workflow can break the mapping. Replacing the placeholder document ID with the correct sheet ID is a required step, and each of the four append nodes needs a valid Google Sheets credential.
Outlook
The template shows a broader trend in automation. Document extraction, once a specialised task, is becoming a standard building block that non-developers can assemble from prepared components. A personal CV database is a modest example, but the same pattern can be applied to invoices, contracts and other recurring documents. For job seekers, the most immediate benefit is time saved on repetitive data entry, along with a cleaner record that can be reused whenever the next application arrives.
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