ResumeSkills
A collection of AI agent skills for resume optimization, job applications, and career development.
- Source repo
- Paramchoudhary/ResumeSkills
- Stars
- ★ 2.8k
- Last updated
- 4mo ago
- License
- MIT
- FA score
- 23/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformCodex · Claude CodeChatGPT (Partial support)
- Cost
- Free software; you pay for model usage
- Setup effort
- Low · running in minutes
- You'll need
- Typical use
- A job seeker uses resume-ats-optimizer to ensure their resume passes ATS filters before applying.
- Not a fit if
- Users who need a standalone app without an external AI assistant
- Non-technical users who cannot install Node.js or run npx
- Teams expecting deterministic, reproducible output quality
- Source review
- 23/100 · Major gaps 8 safety controls not found
What does this agent do, and when should you use it?
ResumeSkills is a collection of skills designed to enable AI coding assistants (such as Claude Code, Cursor, Windsurf) to help users with resume optimization, job applications, and career development. It includes 20 distinct skills covering ATS optimization, resume bullet writing, job description analysis, cover letter generation, interview preparation, salary negotiation, and more. The skills are provided as Markdown files that AI agents can read to gain specialized knowledge and workflows. Installation options include using the npx command-line tool for global or project-level installation, or manually cloning the repository and copying the skills folder. These skills are targeted at job seekers, career changers, and professionals who want to leverage AI in their job search.
The repository provides 20 individual skills, each a Markdown file containing detailed instructions for a specific task. For example, the resume-ats-optimizer skill checks ATS compatibility and optimizes keywords; resume-bullet-writer transforms weak bullets into achievement-focused statements with metrics; job-description-analyzer analyzes job postings, calculates match scores, and identifies gaps. Users can invoke these skills by asking their AI assistant in natural language, such as 'Optimize my resume for ATS' or 'Write me a cover letter for this role.' The AI assistant reads the skill file and applies the framework to produce outputs like optimized resumes, cover letters, or interview questions. Skills are installed via npx skills add Paramchoudhary/ResumeSkills -g -y or manually copying to the skills directory.
- A job seeker uses resume-ats-optimizer to ensure their resume passes ATS filters before applying.
- A professional with a lackluster resume uses resume-bullet-writer to rewrite bullet points with achievements and metrics.
- A career changer uses career-changer-translator to translate skills from their current industry to a new one.
- A candidate with multiple offers uses offer-comparison-analyzer to compare total compensation and benefits.
- A person preparing for an interview uses interview-prep-generator to create STAR stories and practice questions.
- An academic researcher uses academic-cv-builder to format a CV with publications, grants, and teaching experience.
How do you install or deploy this agent?
Recommended CLI install: npx skills add Paramchoudhary/ResumeSkills -g -y (global) or npx skills add Paramchoudhary/ResumeSkills -y (project). Alternatively, manually clone the repo: git clone https://github.com/Paramchoudhary/ResumeSkills.git and copy the skills to the appropriate directory (e.g., ~/.cursor/skills/). Individual skills can also be downloaded directly.
How do you use this agent?
After installation, simply ask your AI assistant in natural language. For instance, 'Optimize my resume for ATS' triggers resume-ats-optimizer; 'Write me a cover letter for this role' uses cover-letter-generator. The assistant automatically loads the relevant skill and applies its workflow.
What are this agent's strengths and limitations?
- Covers the entire job search process from resume optimization to salary negotiation with 20 specialized skills.
- Easy integration with multiple AI assistants via
npx skillsor manual copy. - Skills are modular, allowing users to install only what they need.
- Includes practical examples and quick-start guides to lower the learning curve.
- Depends on external AI assistants (e.g., Claude Code) to execute; no standalone runtime.
- Installation requires Node.js and npx, which may be a barrier for less technical users.
- Effectiveness relies on the AI assistant's understanding; output quality may vary.
- No API or standalone runtime provided; cannot be used as an independent application.
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| ResumeSkills This agent | 23 · Major gaps | Agent plugin / skillFree + model costs | ★ 2.8k | 4mo ago | — | Codex · Claude Code |
| Job Application Agent | 83 · Good | Agent plugin / skillFree | ★ 160 | today | JavaScript | Codex · Claude Code |
| LinkedIn MCP Server | 79 · Good | MCP serverFree | ★ 3.9k | 3d ago | Python | — |
| Three Years of Interviews, Five Years of Practice: AIGC/LLM/AI Agent Interview Knowledge Base | 32 · Major gaps | Web appFreemium | ★ 5k | 2d ago | Python | — |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows the repository contains only README and LICENSE, with no skill files, code, or execution logic. Therefore, permissions, user confirmation, data flow, sensitive data handling, dependency security, external effects, rollback, and source attribution cannot be assessed. All trust criteria score 0 due to lack of evidence.
Self-consistency: The skills listed in README are consistent with descriptions, but actual skill files are not provided, so internal consistency cannot be verified. Dependency availability: Installation relies on 'npx skills' without version pinning or verification, introducing uncertainty. Failure messages: No error handling or failure documentation is provided.
Audience and scenarios: README clearly targets job seekers, career changers, and professionals, listing multiple scenarios. Capability boundaries: No explicit limitations or boundaries of the skills are stated. Trigger precision: Usage examples are given, but precise trigger conditions are not defined. Environment fit: Claims support for multiple AI agents, but no configuration details are provided.
Information architecture: README is well-structured with a table of contents and categories. Install notes: Three installation methods are provided, but not verified. Naming stability: Skill names are consistent in README, but no version control is evident. Examples and FAQ: Usage examples are provided, but no FAQ. Known limitations: Not mentioned. License: MIT license is present. Versioning/changelog: None. Maintenance responsibility: No explicit maintainer is identified.
Output usability: Actual skill files are not provided, so output quality cannot be assessed. Marginal value: Claims of significant improvements are made without evidence. Cost-benefit: No performance or cost data is provided.
Claim traceability: Claims in README (e.g., 75% of resumes rejected by ATS) lack sources. Cross-source corroboration: None. Fact-inference separation: Facts and inferences are not distinguished.
- Not found in source: least-privilege scopingGrant only what the task needs: a dedicated account or read-only token, scoped to specific directories and repos.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: sensitive-data handlingUse dedicated, low-privilege, revocable API keys — never production credentials — and keep secrets out of logs.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Not found in source: disclosed external effectsEstablish which external systems it writes to, sends to or changes, and verify with test accounts or repos before production.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Not found in source: verifiable attributionInstall from the official repo or registry and check the publisher and URL to avoid look-alike packages.
- The repository contains only README and LICENSE, with no actual skill files, so functionality cannot be verified.
- The installation dependency 'npx skills' is not version-pinned, posing supply chain risks.
- Performance claims in README (e.g., 2-3x more interviews) lack supporting data.
FAQ
Do these skills cost money?
Do the skills work with all AI assistants?
How do I uninstall the skills?
npx skills remove <skill-name> or delete the corresponding files from the skills directory.