Skills-4-SE: A curated list of 180+ useful Claude Skills for Software Engineering and resources for customizing AI for SE

by ArabelaTso · Claude Skill · ★ 162

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

claudeclaude-codeclaude-skillsmetaprogrammingsoftware-developmentsoftware-engineering

Quick Facts

Stars162
Forks17
LanguagePython
CategoryClaude Skill
LicenseApache-2.0
Quality Score63/100
Last Updated2026-08-21
Created2026-02-14
Platformsclaude-code, python
Est. Tokens~13k

About Skills-4-SE

✨ Skills-4-SE: Useful Skills for Software Engineering This repository is a comprehensive, reusable, task-oriented Skills collection designed to support software engineering activities across the entire development lifecycle, including: Requirement understanding, system design, implementation, testing, verification, deployment, and maintenance.

Compatible Skills

These tools work well together with Skills-4-SE for enhanced workflows:

  • remind — semantic(0.31)+complementary+rare_topics+same_lang+similar_pop+shared_platform (65%)
  • cat — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)
  • codex-academic-paper-skills — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (63%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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