Preparing your CV
Two CVs sit side by side. One carries a list reading Python, SQL, Excel; in the other the same tools appear inside the story of a job. In GoTeam CV analysis those two do not earn the same item, because the engine does not look at the section heading, it looks at the evidence under it. This guide writes down which item each section is tied to, and which sections are never read at all.
10 fields
The extraction schema carries only ten fields out of a CV: personal details, summary, experience, education, skills, languages, projects, certificates, achievements, publications
49 items
The same fixed checklist is applied to every CV: 12 technical, 11 experience, 9 education, 7 language, 10 potential items
45 items from code
89 percent of the overall score is computed from the CV in code and never asked of the model
Ten sections of a CV are measured: personal details, summary, experience, education, skills, languages, projects, certificates, achievements and publications. The extraction schema carries no field beyond those; a photo, a date of birth, marital status, military service and hobbies enter no evidence item at all. What counts is not the heading of a section, it is the verifiable fact inside it.
The question usually arrives like this: should I add a photo, should I write my hobbies, should I include references. The answer is not a matter of personal taste, it is set by what the side reading your CV can actually read. The GoTeam CV analysis engine carries ten fields out of a document: personal details, summary, experience, education, skills, languages, projects, certificates, achievements and publications. A field the schema does not recognise is not carried, it is dropped.
Whether the heading is in Turkish or English makes no difference; the extraction pipeline treats Deneyim and Experience, Projeler and Projects as the same section. What does make a difference is what is written under the heading. The engine awards no item for seeing the word Experience; the item is earned when a fact can be verified from the sentences beneath it.
The useful question is not which sections should be there, it is which section evidences what. The same fixed list of 49 items is applied to every CV, and 45 of them are computed directly in code. Every section below is tied to specific items on that list, and which one goes where is written down.

The table holds the ten fields the engine recognises. Each row writes the question that field answers and the item lost when the field stays empty. The numbers in brackets are item weights, and each dimension adds up to 100 on its own.
The table is not a list of advice. The rows do not say write this, they say if you do not write this, that question goes unanswered.
| Section | Which question it answers | Item lost when empty (weight) |
|---|---|---|
| Personal details | How do I reach you, where can I see your work | Email and phone together (6), the link item (8). A GitHub or portfolio link is counted a second time in the technical dimension (6). |
| Summary | In short, what do you do | The item for a summary section describing yourself (8). |
| Experience | Where, for how long, and what did you do | A professional record (10), three duration thresholds (10, 10, 8), a month and year date (10), a start date on every record (6), a description (8), a numeric outcome (12), more than one employer (6). |
| Education | Which school, which department, which degree | An education record (12), the degree name (10), bachelor level or above (14), postgraduate (10), the department name (12), the school name (8), the year (12), the grade average (12), graduation (10). |
| Skills | Which tools and methods do you use | A skill list (6), five skills (8), ten skills (6). Tying the list to usage is two separate items (14 and 12), and a tool name appearing inside a narrative is a third (14). |
| Languages | Which language do you know at which level | A language record (14), a level statement (18), a formal scale (18), B2 or above (16), C1 or above (14), a second language (10), a language certificate (10). |
| Projects | What did you build on your own | A project record (10), a project with its tools written down (8), a project with a link (6), more than one tool in a single record (8). |
| Certificates | What did you certify and when | A certificate record in technical (6) and in potential (8). Being dated within the last five years is a separate item (14). |
| Achievements | Do you have a standout result | The item for an achievement, award or ranking (10). |
| Publications | Have you written or presented in your field | The item for a publication, blog post or talk (6). |
If an experience record has no start date, or the date cannot be read, that record cannot enter the duration calculation. The record is not ignored, the professional experience item is still earned. But because it is not added to the total duration, the three items looking at the 1, 2 and 4 year thresholds are affected.
If no month can be derived from any professional experience, the total duration comes back empty and all three threshold items are lost at once, with the reason that professional duration cannot be computed from the dates. That is how 28 weight units of the experience dimension become invisible. The cause is not a lack of experience, it is a date that cannot be read.
A range written with years only (2024 - 2026) is read, but the system pins it to the first month of the year and flags it with six months of uncertainty. Writing month and year earns its own item (10); having a start date on every record is a second item (6).

The skills section is the easiest part of a CV to lengthen, and that is exactly why it is the weakest evidence. The engine puts every skill into one of four classes: tied to a work record, tied to a project, tied to an education record, or list only. When a skill appears in more than one place, the strongest source is assigned.
Skills that stay list only are gathered under a separate heading in the report: claimed competencies. Next to it sits a single action sentence, write one line about a job where you used that skill. Lengthening the list does not solve this, it multiplies it.
The weights say the same thing. Listing a skill earns an item with a weight of 6, while the same skill appearing in an experience or project narrative is a separate item with a weight of 14. On top of that there is a 12 weight item asking that at least half of the listed skills appear in usage: inflate the list and that ratio drops, and the item is lost.

The education section produces not one item but nine, and all nine are deterministic: is there a record, is the degree name written, is it bachelor level or above, is there a postgraduate degree, is the department name written, is the school name written, is the year written, is the grade average written, was the degree completed.
The practical outcome: a line reading A University, 2019 - 2023 earns the school and year items and loses the department item (12). Adding Computer Engineering, BSc to the same line satisfies two more.
The grade average item (12) only looks at whether it is written, not at its value. The common advice is to hide a low average; the behaviour measured here contradicts it. The decision is yours, but an average left unwritten does not close that item.

The overall score is gathered not from one list but from five dimensions, and the dimension weights are the same for everyone. How much a section affects the overall score depends on two things: which dimensions it feeds and how much that dimension weighs.
A section appearing on more than one row is not a mistake. Certificates feed both the technical and the potential dimension, and so do projects; that is why the same record can be counted in two separate items.
| Dimension | Weight | Sections that feed it | Items |
|---|---|---|---|
| Technical competency | 30 percent | Skills, projects, certificates, experience narrative, portfolio link | 12 |
| Experience | 30 percent | Work experience: dates, descriptions, numeric outcomes, number of employers | 11 |
| Education | 15 percent | Education records | 9 |
| Language skills | 10 percent | Languages: the level statement and a language certificate | 7 |
| Potential | 15 percent | Summary, projects, achievements, certificates, publications, contact details and links | 10 |
Even on the four items that go to the model, what is asked for is not a score but a binary answer: is this written in the CV. The model gives no score, it says item by item whether it is evidenced and leaves a verbatim quote from the CV; the arithmetic is done in code.
Two of those four items require evidence of usage. Appearing in the skill list is not enough, and if the evidence type comes back as a claim, the call becomes missing. The deterministic call also overwrites the model answer: a fact computed in code cannot be changed by the model.
The report draws two lists separately: competencies with evidence found, and those only claimed. The split comes from where the skill name appears, not from how many times it appears. If a tool name appears in a work record, that record becomes the evidence; if it only sits in a list, there is no evidence.
There is a second threshold. Even when a skill appears in a work record, if that record carries no sentence describing what you did, the report flags it as incomplete too. Putting the name of a tool next to a job is not enough, the job has to be put into a sentence.
Some sections common in Turkish CV templates have no counterpart in this engine. A photo, date of birth, marital status, military service status, nationality, references, hobbies and interests are not in the extraction schema. The schema drops a field it does not recognise instead of carrying it, so these sections neither earn nor cost an item.
That does not add up to do not write them. What it adds up to is this: these sections take up space on the page and contribute nothing to the measured items. If your space is limited, what to put in place of what is no longer guesswork, it is a choice with a written consequence.
There is one more limit, and it is about the file rather than the score: on the candidate side only a PDF is accepted, at most 5 MB and by default 15 pages. A Word file is exported as PDF and then uploaded. The document passes an integrity gate first, so a file that is not a CV stops at the gate.

A frequent mistake: writing Python, Java and SQL under a Languages heading. The extraction pipeline forbids that outright, programming languages belong in the skills section. The Languages section carries spoken languages; a tool name written in the wrong place feeds no language item.
Language details do not have to sit under a heading of their own, though. If a language appears anywhere in the CV (on a skills line, inside the summary), it is extracted. The only requirement is that the level is written.
How you write the level separates two different items. English: good level satisfies the level statement item (18) but not the formal scale item (18). English: C1 satisfies both and brings the third item looking at the C1 threshold (14) as well.
CVs that put freelance work under Experience and work records under Projects are common, and both land on the wrong side. The extraction pipeline draws the line by looking at the section heading, company markers (Inc, Ltd, A.Ş.), a formal job title and the presence of dates.
Every record under a Projects heading counts as a project and does not enter professional duration. If you want a piece of work counted as duration, that record has to sit under the experience heading with an employer name, a title and a date.
The engine reads ten fields from a CV: personal details, summary, experience, education, skills, languages, projects, certificates, achievements and publications. Nothing outside those enters an evidence item. Absolutely is not an obligation here, it is the edge of the measured surface: a section you do not write is not read, and a section you do write only earns an item if it holds a verifiable fact.
We have no measured answer to that. The only thing we can say is that a photo is not in the extraction schema: it enters no evidence item, and it neither earns nor costs anything. What a photo does to a human reader is a separate question and our measurement does not cover it.
No. Internship records stay in the CV and are read, they simply do not enter the professional duration calculation; they fall into a separate class. The same holds for volunteer work and personal projects. What to do is not delete them, it is to show professional experience under a heading separate from the internship records.
The engine only looks at whether it is written, not at its value; when it is left out, the 12 weight item in the education dimension is lost outright. The common advice is to leave a low average out, and that advice contradicts the behaviour measured here. The product own action sentence carries the tension too: add it if it is good, and it cannot join the score when it is not written.
Only up to a point. Two items look at the five and ten skill thresholds, but there is also a 12 weight item asking that at least half of the listed skills appear in an experience or project narrative. Padding the list with tools you have not used lowers that ratio and loses the item. Tying the tools already on the list to a narrative satisfies more items than lengthening the list does.
No. Extraction recognises sections from their headings, knows the Turkish and English headings alike, and the order enters no item; the same file always gets the same score. What the order does to a human reader is outside our measurement, so there is no ordering advice here.