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Get Started Free →Optimize resumes for Applicant Tracking Systems, check ATS compatibility, and analyze keyword match. Use when the user mentions ATS, applicant tracking, keyword optimization, parsing, or getting past resume screening software.
.claude/skills/davila7-resume-ats-optimizer/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 79% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 132% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 104% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 135% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 184% | 0% |
Use this skill when the user wants to:
Also use when the user provides a resume file and mentions they're applying to jobs.
75% of resumes are rejected by Applicant Tracking Systems before a human ever sees them. Companies use ATS to:
Common reasons resumes fail ATS:
Use standard, recognizable headers:
John Smith
email@example.com | (555) 123-4567 | LinkedIn: linkedin.com/in/johnsmith
San Francisco, CANOT in header/footer, and avoid:
Identify three types of keywords:
Hard Skills (Technical)
Soft Skills
Industry Terms
For each keyword in job description:
Match Score = (Keywords Matched / Total Required Keywords) × 100
Example:
Job has 20 required keywords
Your resume has 15 of them
Match Score = 75%
Target: 80%+ for strong matchPriority 1: Professional Summary (Top of Resume)
Priority 2: Skills Section
Priority 3: Experience Bullets
Keyword Density Guidelines:
When analyzing a resume, provide this structured report:
markdown# ATS COMPATIBILITY REPORT ## Overall Score: [X]/100 ### File Format Check ✅/❌ - Format: [DOCX/PDF] - Text extraction: [Success/Failed] - File size: [X KB/MB] ### Formatting Issues ✅ No tables or columns detected ❌ Contact info in header (move to body) ⚠️ Two different font sizes in skills section ### Keyword Analysis JOB REQUIREMENTS vs YOUR RESUME: **Critical Keywords (Must Have):** ✅ Project Management - Found 3x ✅ Agile/Scrum - Found 2x ❌ Stakeholder Management - MISSING (mentioned 5x in JD) ❌ Budget Management - MISSING (mentioned 3x in JD) **Important Keywords:** ✅ Cross-functional teams - Found 1x ⚠️ "Risk management" - You have "risk mitigation" (close but not exact match) ✅ Process improvement - Found 2x **Match Score: 65%** Target: 80%+ recommended ### Recommended Changes **1. Add Missing Keywords:** In Professional Summary, change: "Experienced project manager with proven track record..." To: "Experienced project manager with proven track record in stakeholder management and budget oversight..." In Experience section, add bullet: "Managed stakeholder communication across 3 departments and executive leadership team" "Directed budget management for $2.5M project portfolio" **2. Fix Formatting:** - Move contact information from header to body of resume - Make all skill section items same font size (currently 10pt and 11pt mixed) **3. Strengthen Existing Keywords:** Change "risk mitigation" to "risk management" for exact match ### Estimated New Match Score: 85%
❌ PROBLEM:
[Two-column layout with graphics]
[Skill bars and proficiency charts]
[Text in colored boxes]
✅ SOLUTION:
- Single column layout
- Text-only skills list
- Simple bullet points❌ PROBLEM:
"My Journey" (instead of Experience)
"What I Bring to the Table" (instead of Skills)
"Academic Pursuits" (instead of Education)
✅ SOLUTION:
Use standard headers ATS recognizes❌ PROBLEM:
Job requires: "Python, SQL, Data Visualization"
Resume says: "Programming, databases, making charts"
✅ SOLUTION:
Use exact terminology from job description❌ PROBLEM:
Skills: Python, Python programming, Python developer, Python expert, Python specialist, Advanced Python...
✅ SOLUTION:
Skills: Python, SQL, JavaScript, React, Node.js
(Then incorporate naturally in bullets)When helping user optimize for ATS:
After optimization, the resume should:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 14,041 | 15,357 | +9% | 1 | 1 | 0% | 2,603 | 4,931 | +89% | 0 | 0 | — |
case-02 | fail→fail | 8,150 | 4,318 | -47% | 1 | 1 | 0% | 1,429 | 2,902 | +103% | 0 | 0 | — |
case-03 | fail→pass | 12,256 | 7,644 | -38% | 1 | 1 | 0% | 1,938 | 3,463 | +79% | 0 | 0 | — |
case-04 | pass→pass | 7,376 | 3,154 | -57% | 1 | 1 | 0% | 1,280 | 2,704 | +111% | 0 | 0 | — |
case-05 | pass→pass | 7,498 | 4,429 | -41% | 1 | 1 | 0% | 1,372 | 2,899 | +111% | 0 | 0 | — |
case-06 | pass→pass | 9,306 | 5,256 | -44% | 1 | 1 | 0% | 1,505 | 3,088 | +105% | 0 | 0 | — |
case-07 | pass→pass | 8,254 | 4,531 | -45% | 1 | 1 | 0% | 1,350 | 2,847 | +111% | 0 | 0 | — |
case-08 | fail→pass | 9,105 | 7,953 | -13% | 1 | 1 | 0% | 1,506 | 3,498 | +132% | 0 | 0 | — |
case-09 | pass→pass | 8,096 | 4,961 | -39% | 1 | 1 | 0% | 1,535 | 2,920 | +90% | 0 | 0 | — |
case-10 | fail→pass | 9,382 | 6,412 | -32% | 1 | 1 | 0% | 1,564 | 3,183 | +104% | 0 | 0 | — |
case-11 | fail→pass | 7,187 | 5,790 | -19% | 1 | 1 | 0% | 1,396 | 3,286 | +135% | 0 | 0 | — |
case-12 | pass→pass | 10,945 | 11,418 | +4% | 1 | 1 | 0% | 1,824 | 3,935 | +116% | 0 | 0 | — |
case-13 | pass→pass | 8,867 | 6,588 | -26% | 1 | 1 | 0% | 1,466 | 3,162 | +116% | 0 | 0 | — |
case-14 | fail→pass | 7,510 | 8,430 | +12% | 1 | 1 | 0% | 1,240 | 3,523 | +184% | 0 | 0 | — |
case-15 | pass→pass | 8,975 | 7,431 | -17% | 1 | 1 | 0% | 1,500 | 3,425 | +128% | 0 | 0 | — |
case-16 | pass→pass | 9,469 | 9,437 | -0% | 1 | 1 | 0% | 1,635 | 3,526 | +116% | 0 | 0 | — |
case-17 | pass→pass | 13,885 | 11,552 | -17% | 1 | 1 | 0% | 2,328 | 4,372 | +88% | 0 | 0 | — |
case-18 | pass→pass | 9,587 | 8,042 | -16% | 1 | 1 | 0% | 1,592 | 3,574 | +124% | 0 | 0 | — |
case-19 | pass→pass | 9,451 | 8,912 | -6% | 1 | 1 | 0% | 1,584 | 3,536 | +123% | 0 | 0 | — |
case-20 | pass→pass | 10,791 | 11,976 | +11% | 1 | 1 | 0% | 1,795 | 4,044 | +125% | 0 | 0 | — |
case-21 | pass→pass | 9,861 | 6,542 | -34% | 1 | 1 | 0% | 1,568 | 3,193 | +104% | 0 | 0 | — |
case-22 | pass→pass | 12,521 | 10,013 | -20% | 1 | 1 | 0% | 2,113 | 3,814 | +81% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +23 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.