Resume KeywordsFree — No Signup Required

1. 1Copy the full job description, not just the title
2. 2Highlight every tool, technology, and platform named (AWS, PostgreSQL, Salesforce, GA4)
3. 3Highlight requirement phrases ('project management,' 'SOC 2 compliance')
4. 4Separate 'Required' from 'Preferred' — required terms matter most
5. 5Note the role's level language (lead, senior, staff) to align your summary

• Professional summary — 2–3 of the role's core terms in one or two sentences
• Skills section — explicit plain-text list of hard skills and tools
• Experience bullets — name the stack you used per project ('Built REST APIs in Go handling 15K RPS')
• Education and certifications — exact names of degrees and certificates

Run your resume through a keyword scanner and ATS checker against the specific job description. If required skills are still missing, add them in context — never in white text or invisible lists. Re-scan until required terms register.

Every profession has predictable keyword clusters. Use these as a checklist when a job description is vague, then confirm against the specific posting.

Most ATS software matches literal text, not meaning. 'Project management' does not match 'program management,' and 'CRM' may not match 'Salesforce' unless the description uses both. The safest pattern: mirror the job description's exact phrasing, then add the common acronym or full form once where it fits naturally.

• White-text or hidden keyword lists — modern parsers detect invisible text, and recruiters can too
• Listing skills you do not have — you pass the ATS and fail the interview
• Keyword-stuffing one bullet — unnatural density reads as noise to both systems and humans
• Forgetting to mirror exact JD phrasing — synonyms do not count as matches in literal matching
• Putting keywords only in the summary — they must appear where the skill was actually used

The exact mechanics differ by vendor, but the core loop is the same everywhere — and knowing it explains why placement matters as much as presence.

1. 1The job description is tokenized into terms: skills, tools, certifications, and requirement phrases
2. 2Your resume is parsed into the same token stream from its extracted text
3. 3Terms are matched literally first — exact phrase and word matches score highest
4. 4Frequency and placement weight terms: required skills and summary/skills-section hits score more
5. 5The system produces a match percentage used to rank you against other applicants

More keywords is not automatically better. Density that reads naturally signals genuine experience; density that reads like a checklist signals stuffing to both systems and recruiters.

1. 1Paste the JD into a keyword scanner and list every missing term
2. 2Group missing terms into skills, tools, and phrases
3. 3Add the truthful ones where they fit naturally — skills list first
4. 4Weave the most important phrases into bullets with context
5. 5Re-scan and repeat until required terms register
6. 6Confirm you can speak to every added term in an interview