tech-resume-optimizer

tech-resume-optimizer is a skill for Claude Code, Codex from Paramchoudhary/ResumeSkills. It costs 17 tokens per session (2,485 once invoked), scanned A, original, MIT.

A guide for improving resumes aimed at software, product-management, data, and other technical jobs. It focuses on presenting technical skills, projects, achievements, and links clearly for recruiters and automated screening systems.

In plain words
What is it for?
Use it to revise technical skills sections, describe projects and results, structure work history, and prepare resumes for technical recruiters and applicant-tracking systems.
Why use it?
Technical resumes can be difficult to balance: they must show enough detail while explaining why the work mattered. This helps turn experience into clearer, more relevant application material.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to revise technical skills sections, describe projects and results, structure work history, and prepare resumes for technical recruiters and applicant-tracking systems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/paramchoudhary/resumeskills/tech-resume-optimizer
About the project

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.

Paramchoudhary/ResumeSkills · 2,169 stars · on GitHub

Install

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.

Any agent
npx skills add Paramchoudhary/ResumeSkills --skill tech-resume-optimizer
Clone the repo
git clone --depth 1 https://github.com/Paramchoudhary/ResumeSkills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for tech-resume-optimizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/paramchoudhary/resumeskills/tech-resume-optimizer.svg)](https://agentmods.dev/skills/paramchoudhary/resumeskills/tech-resume-optimizer)
Your own site
<a href="https://agentmods.dev/skills/paramchoudhary/resumeskills/tech-resume-optimizer"><img src="https://agentmods.dev/badge/skills/paramchoudhary/resumeskills/tech-resume-optimizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,485 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 23 May 2026
  • Snyk pass 23 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00017 $0.02485
Opus 5 $0.00009 $0.01242
Sonnet 5 $0.00003 $0.00497
Haiku 4.5 $0.00002 $0.00248

Measured 8d ago against content hash 38cbc83d7d14, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

tech-resume-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 8d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

skills/tech-resume-optimizer/SKILL.md · 371 lines

How it starts

The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tech Resume Optimizer

When to Use This Skill

Use this skill when the user:

  • Is applying for software engineering roles
  • Wants to optimize a technical resume
  • Needs help with developer/PM/technical job applications
  • Mentions: "tech resume", "software engineer resume", "developer resume", "technical resume", "SWE resume", "PM resume"

Core Capabilities

  • Optimize resumes for technical roles (SWE, PM, Data, DevOps)
  • Structure technical skills sections effectively
  • Highlight projects and technical achievements
  • Balance technical depth with business impact
  • Format for both ATS and technical recruiters
  • Include GitHub, portfolio, and technical links

Tech Resume Philosophy

What Tech Recruiters Look For:

  1. Relevant technical skills (languages, frameworks, tools)
  2. Scale and impact (users, transactions, data size)
  3. Problem-solving abilities
  4. System design understanding
  5. Collaborative abilities
  6. Growth trajectory

Tech Resume Structure

Recommended Order

1. Contact Information (including GitHub, Portfolio)
2. Professional Summary (optional but helpful)
3. Technical Skills (critical for ATS)
4. Work Experience (with technical achievements)
5. Projects (especially for early career)
6. Education
7. Certifications (if relevant)

Contact Section for Tech

John Developer
San Francisco, CA
[email protected] | (555) 123-4567
LinkedIn: linkedin.com/in/johndev
GitHub: github.com/johndev
Portfolio: johndev.io

Include:

  • GitHub (required for SWE roles)
  • Portfolio/personal website
  • LinkedIn
  • Tech blog (if you have one)

Don't Include:

  • Address (city/state is enough)
  • Photo
  • Social media (unless relevant)

Technical Skills Section

Organization Strategies

Option 1: By Category

Languages: Python, JavaScript, TypeScript, Go, SQL
Frameworks: React, Node.js, Django, FastAPI
Databases: PostgreSQL, MongoDB, Redis, Elasticsearch
Cloud/Infrastructure: AWS (EC2, S3, Lambda, RDS), Docker, Kubernetes, Terraform
Tools: Git, JIRA, CI/CD, Datadog, Grafana

Read the full file on GitHub · 371 lines

Changes

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.

  1. 8d ago First seen · 371 lines · 17 tokens per session scan A 38cbc83d7d14

Subscribe to this mod's changes

tech-resume-optimizer is a skill published in the GitHub repository Paramchoudhary/ResumeSkills (2,169 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 2,485 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.

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