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 art2url/career-agent-skills --skill software-engineer-resumegit clone --depth 1 https://github.com/art2url/career-agent-skillsWrote 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/art2url/career-agent-skills/software-engineer-resume)<a href="https://agentmods.dev/skills/art2url/career-agent-skills/software-engineer-resume"><img src="https://agentmods.dev/badge/skills/art2url/career-agent-skills/software-engineer-resume/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/art2url/career-agent-skills/software-engineer-resume"><img src="https://agentmods.dev/badge/skills/art2url/career-agent-skills/software-engineer-resume.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 | $0.00033 | $0.00842 |
| Opus 5 | $0.00016 | $0.00421 |
| Sonnet 5 | $0.00007 | $0.00168 |
| Haiku 4.5 | $0.00003 | $0.00084 |
Grade A, and why
software-engineer-resume 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Software Engineer Resume
Trigger
Use when the user is applying for technical roles: software engineering, data engineering/science, DevOps/SRE, or technical PM.
Keywords: "software engineer resume", "developer resume", "SWE resume", "tech resume", "engineering resume", "data science resume", "DevOps resume", "backend developer resume", "frontend developer resume", "full stack resume", "programmer resume", "GitHub profile", "technical skills section", "coding resume", "IT resume", "software developer resume"
Structure
Recommended section order:
- Contact — include GitHub and portfolio links
- Summary — optional, helpful for senior roles
- Technical Skills — critical for ATS
- Experience — technical achievements with scale
- Projects — especially important for early career
- Education
- Certifications — if relevant
Process
Step 1: Structure Technical Skills
Organize by category:
Languages: Python, TypeScript, Go, SQL
Frameworks: React, Node.js, FastAPI, Django
Databases: PostgreSQL, Redis, MongoDB, Elasticsearch
Cloud/Infra: AWS (EC2, S3, Lambda), Docker, Kubernetes, Terraform
Tools: Git, GitHub Actions, Datadog, Grafana
Rules:
- Only list tech you can discuss in an interview
- Order by relevance to target role
- Be specific on cloud (list services, not just "AWS")
- Omit: Microsoft Office, operating systems (unless DevOps), skill bars/ratings, tech you touched once
Step 2: Write Technical Bullets
Formula: [Action Verb] + [Technical What] + [Scale/Performance] + [Tech Used]
Key metrics:
- Scale: DAU/MAU, requests/sec, data volume (TB/day)
- Performance: latency reduction, uptime %, load time
- Efficiency: cost savings, deployment time, automation hours saved
- Business: revenue impact, conversion improvement, user growth
Examples:
- SWE: "Architected auth microservice (OAuth 2.0, JWT) serving 500K+ DAU, reducing login latency from 5s to 2s"
- Data: "Built ETL pipeline processing 100M+ events/day (Kafka, Spark), reducing data latency from hours to minutes"
- DevOps: "Implemented IaC with Terraform, reducing provisioning from 2 days to 30 minutes across 200+ services"
- Tech PM: "Led API platform roadmap for 10K+ developers, driving 40% increase in API adoption"
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.
- 12d ago First seen · 107 lines · 33 tokens per session scan A ada4e35d9f4b
software-engineer-resume is a skill published in the GitHub repository art2url/career-agent-skills (9 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 842 once invoked, about $0.0002 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 2026-08-31.
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