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 Natsummerance/readMD --skill tech-resume-optimizergit clone --depth 1 https://github.com/Natsummerance/readMDWrote 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/natsummerance/readmd/tech-resume-optimizer)<a href="https://agentmods.dev/skills/natsummerance/readmd/tech-resume-optimizer"><img src="https://agentmods.dev/badge/skills/natsummerance/readmd/tech-resume-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/natsummerance/readmd/tech-resume-optimizer"><img src="https://agentmods.dev/badge/skills/natsummerance/readmd/tech-resume-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00017 | $0.02485 |
| Opus 5.5 | $0.00007 | $0.00994 |
| Sonnet 5.5 | $0.00003 | $0.00497 |
| Haiku 4.5 | $0.00002 | $0.00248 |
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 1mo 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.
This is a copy
100% identical to tech-resume-optimizer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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:
- Relevant technical skills (languages, frameworks, tools)
- Scale and impact (users, transactions, data size)
- Problem-solving abilities
- System design understanding
- Collaborative abilities
- 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
- 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
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.
- 1mo ago First seen · 371 lines · 17 tokens per session scan A 38cbc83d7d14
tech-resume-optimizer is a skill published in the GitHub repository Natsummerance/readMD (26 stars, last pushed 16d ago), licensed MIT. It adds 17 tokens to every session and 2,485 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to tech-resume-optimizer, differing in 0 lines, and is treated as a copy.
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