re-skill: Claude Code skill for reverse engineering retro games — disassemble, annotate, extract assets, web port

by vgrichina · Claude Skill · ★ 170

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

Security audit verdict: SAFE · quality 70/100

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.

Quick Facts

Stars170
Forks13
LanguageShell
CategoryClaude Skill
LicenseMIT
Quality Score70/100
Last Updated2026-03-05
Created2026-03-05
Platformsbrowser, claude-code, cli
Est. Tokens~3k

About re-skill

/re — Reverse Engineering Skill for Claude Code A Claude Code skill that bootstraps and drives retro game reverse-engineering projects. Point it at a ROM or binary, and it scaffolds a full RE workspace — then iteratively disassembles, annotates, extracts assets, and ports the game to a web canvas, all from the CLI.

Compatible Skills

These tools work well together with re-skill for enhanced workflows:

  • iOS-reverse-engineering-claude-skill — semantic(0.44)+shared_fw(anthropic)+same_lang+similar_pop+shared_platform (58%)
  • spectral — semantic(0.28)+complementary+shared_fw(anthropic)+similar_pop+shared_platform (58%)
  • -awesome-cc-harness — semantic(0.27)+complementary+shared_fw(anthropic)+similar_pop+shared_platform (57%)
  • CLI-Anything-WEB — semantic(0.24)+complementary+shared_fw(anthropic)+similar_pop+shared_platform (56%)

re-skill alternative? Top 2 similar tools

Looking for a re-skill alternative? If you're comparing re-skill with other claude skill tools, these 2 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • claude-ai-mcp by anthropics · ⭐ 484

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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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