ResumeSkills is a collection of AI-agent skills for improving resumes, preparing job applications, practicing interviews, and planning career moves. It is intended for job seekers, career changers, and professionals using Claude Code for tasks such as ATS checks, job-description matching, resume tailoring, and salary negotiation. The catalogue entry consists of the project's career-focused skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Paramchoudhary/ResumeSkills --skill resume-ats-optimizergit clone --depth 1 https://github.com/Paramchoudhary/ResumeSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/paramchoudhary/resumeskills/resume-ats-optimizer)<a href="https://agentmods.dev/skills/paramchoudhary/resumeskills/resume-ats-optimizer"><img src="https://agentmods.dev/badge/skills/paramchoudhary/resumeskills/resume-ats-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/paramchoudhary/resumeskills/resume-ats-optimizer"><img src="https://agentmods.dev/badge/skills/paramchoudhary/resumeskills/resume-ats-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.02091 |
| Opus 5 | $0.00010 | $0.01045 |
| Sonnet 5 | $0.00004 | $0.00418 |
| Haiku 4.5 | $0.00002 | $0.00209 |
Grade A, and why
resume-ats-optimizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- resume-ats-optimizer — 100% identical, 0 lines differ
- resume-ats-optimizer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume ATS Optimizer
When to Use This Skill
Use this skill when the user wants to:
- Optimize their resume for Applicant Tracking Systems (ATS)
- Check if their resume will pass automated screening
- Understand why their applications aren't getting responses
- Mentions keywords like: "ATS", "not getting interviews", "resume not working", "optimize resume", "keyword optimization"
Also use when the user provides a resume file and mentions they're applying to jobs.
Core Capabilities
- Parse resume and test ATS compatibility
- Extract and analyze keywords against job descriptions
- Identify formatting issues that break ATS parsers
- Calculate match scores between resume and job postings
- Suggest keyword additions and placements
- Generate ATS-friendly formatting recommendations
The ATS Problem
75% of resumes are rejected by Applicant Tracking Systems before a human ever sees them. Companies use ATS to:
- Filter out unqualified candidates automatically
- Search for specific keywords from job requirements
- Parse resumes into structured data
- Rank candidates by keyword match percentage
Common reasons resumes fail ATS:
- Poor formatting (tables, columns, headers/footers)
- Missing keywords from job description
- Inconsistent section headers
- Non-standard fonts or special characters
- Text embedded in images
- Incorrect file format
ATS Compatibility Checklist
File Format
- ✅ Use .docx or .pdf (not .pages, .odt)
- ✅ PDF must be text-based, not scanned image
- ✅ File name: "FirstName_LastName_Resume.pdf"
Font & Formatting
- ✅ Standard fonts: Arial, Calibri, Georgia, Times New Roman
- ✅ Font size: 10-12pt for body, 14-16pt for headers
- ✅ No text boxes, tables, or columns
- ✅ No headers/footers (put contact info in body)
- ✅ No images, graphics, or charts
- ✅ Consistent date formats (MM/YYYY)
- ✅ Standard bullet points (•, -, *)
Section Headers
Use standard, recognizable headers:
- ✅ "Professional Experience" or "Work Experience" (not "Where I've Been")
- ✅ "Education" (not "Academic Background")
- ✅ "Skills" (not "Core Competencies")
- ✅ "Summary" or "Professional Summary"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 320 lines · 21 tokens per session scan A 03ad07d45afa
resume-ats-optimizer is a skill published in the GitHub repository Paramchoudhary/ResumeSkills (2,190 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 2,091 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…