Most resumes silently fail ATS filters due to repeated opening verbs, weak filler phrases, and low bullet diversity. Resume Repetition Checker surfaces every pattern instantly — no scoring, no AI, just real deterministic parsing.
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Bullet Input
Managed a team of 8 engineers across two dep…
Responsible for daily standups and sprint pl…
Managed vendor relationships with various st…
Successfully led migration of several legacy…
Managed deployment pipelines and code review…
Parser Warnings
Opening verb appears 3 times. ATS parsers flag low verb…
Passive-weak opener. Replace with a direct action verb.…
"various" adds no measurable context. Replace with spec…
Implied by the outcome. Remove or replace with a metric…
The Problem
Recruiters scan 50+ resumes per role. A resume with "Managed" opening six bullets reads as low-effort. ATS parsers also detect keyword stuffing and reduce relevance scoring for patterns they flag as automated or low-quality content.
How It Works
Drop your resume bullets into the tool. One per line or pasted directly from your resume. No formatting required.
The repetition engine runs entirely in your browser. No server receives your data. No upload, no account.
Every repeated verb, weak phrase, and filler word is flagged with severity, context, and replacement suggestions.
Features
Every check reflects something real ATS systems and recruiters flag in practice.
Detects when the same action verb opens multiple bullets. Flags frequency and recommends replacements.
Catches 'responsible for', 'worked on', 'helped with', and similar passive-weak constructions.
Surfaces 'various', 'numerous', 'successfully', and other vague terms that reduce ATS relevance.
Identifies structural monotony where every bullet follows the same opening pattern.
Flags passive constructions like 'was led by' or 'were implemented by' that reduce bullet impact.
Detects when the same keyword or phrase appears excessively across your resume bullets.
Shows the ratio of unique opening verbs to total bullets. Ideal: one unique verb per bullet.
Every issue comes with concrete alternatives — not generic advice, but contextually relevant options.
Rule-Based Logic
Every check runs on deterministic logic: fixed pattern matching, frequency analysis, and structural parsing. There is no language model making inferences. You see exactly what the rules caught and why.
This means outputs are reproducible and explainable. The same resume always produces the same output. No randomness, no hallucination.
opener_count[verb] >= 3 → CRITICALopener_count[verb] === 2 → MEDIUMline.includes(WEAK_OPENERS[i]) → flagfiller_re.test(line) → LOW or MEDIUM/was.*by/i.test(line) → MEDIUMFAQ
No. Every check is rule-based and deterministic. Pattern matching, frequency counting, and structural parsing — nothing probabilistic.
No. All parsing runs client-side in your browser using JavaScript. Nothing is transmitted to any server.
ATS parsers extract structure from resume bullets. Low verb diversity is a signal of low-effort or templated content. Some ATS platforms also reduce relevance scoring for keyword-stuffed sections.
The tool handles standard resume sections — typically 15–30 bullets. For longer resumes, paste by section.
Words like 'various', 'numerous', 'several', 'successfully', and 'effectively' that add length without adding measurable meaning. Replace them with specifics.
Yes. Recruiters scan quickly. A resume opening the same verb six times reads as low-effort. Strong resumes show verb diversity and specificity from the first word of every bullet.
CRITICAL: patterns repeated 3+ times or weak openers on multiple bullets. MEDIUM: patterns repeated twice or passive constructions. LOW: single-instance filler words or minor issues.
Related Tools
Find every repeated verb, weak phrase, and filler word instantly. Free, browser-based, no signup.
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