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Ivy League AI Resume Builder
Build and audit ATS-safe, Ivy League-standard resumes using quantified STAR-method bullets and elite career guidelines.
$5.95
Ivy League AI Resume Builder
Example session with this skill installed
I'm applying for a Senior Product Manager role at Google. Here is my current resume text. Can you review it and rewrite my bullets to be more impactful and ATS-friendly?
- Read your context and instructions
- Compiled the ivy league ai
I have audited your resume text against Ivy League career-services standards. The mechanical audit flagged three personal pronouns and several bullets lacking quantification. I have restructured your experience to emphasize scale and product impact.
Resume Critique & Rewrites
| Section | Assessment |
|---|---|
| Visual/ATS | Single-column text is safe, but your contact header is missing a LinkedIn URL. |
| Action Verbs | Currently uses "Responsible for" and "Assisted with." Needs stronger lead verbs. |
| Quantification | Only 20% of bullets have numbers. High-priority fix for FAANG roles. |
Suggested Bullet Rewrites
- Before: Responsible for managing the product roadmap and talking to customers.
After: Led product roadmap for a [X]-user platform, conducting 50+ customer interviews to prioritize features that grew MAU by [Y%].
- Before: Helped the engineering team fix bugs faster.
After: Streamlined cross-functional sprint cycles, reducing average bug resolution time by 15% through the implementation of a new triaging system.
Numbers to fill in
- What was the total user base of the platform you managed?
- What was the specific percentage increase in Monthly Active Users (MAU)?
- How many engineers were in the team you supported?
Next steps
- Provide the missing metrics listed above.
- Confirm if you want me to generate the final ATS-safe
.docxfile. - Send the specific Google job description for final keyword optimization.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Most resumes fail because they use multi-column layouts that break ATS parsers or rely on weak, non-quantified descriptions. Recruiters spend less than 20 seconds on a first pass, and decorative templates often hide the candidate's actual impact.
What it does
- Performs a mechanical audit of existing resumes to catch pronouns, passive verbs, and formatting errors.
- Rewrites weak experience bullets into high-impact STAR-method statements with quantified results.
- Generates single-column, ATS-safe .docx files using Ivy League career service standards.
- Tailors section order and emphasis based on career stage and specific target industries like Finance, Tech, or Academia.
Frameworks & tools
Python-docx for document generation, pdfplumber for layout analysis, and standardized JSON schemas for resume data structure.
Why this beats prompting it yourself
Generic LLM prompts often hallucinate metrics or use flowery, "AI-sounding" language that recruiters spot instantly. This skill enforces a strict "no-fabrication" rule, uses specialized scripts to verify mechanical compliance, and follows specific formatting conventions from Harvard, Yale, and UPenn.
Use cases
- Converting a messy LinkedIn export into a professional, one-page finance resume.
- Auditing a technical CV to ensure skills are properly positioned for ATS keyword matching.
- Transforming vague job duties into quantified achievements for a senior management role.
- Fixing layout issues in a PDF resume that is failing to parse in application portals.
Known limitations
Does not support multi-column or highly graphic "creative" layouts. Requires manual input for missing metrics to avoid factual hallucinations.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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