functional-emotions-video: A painted music video for Functional Emotions, made by Claude Opus 5.5

by ledbetterljoshua · AI Tool · ★ 78

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

Featured in: Claude Video Editing & Remotion Skills

Security audit verdict: SAFE · quality 58/100

None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

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

Stars78
Forks7
LanguageJavaScript
CategoryAI Tool
LicenseMIT
Quality Score58/100
Last Updated2026-09-23
Created2026-09-23
Platformsclaude-code, node
Est. Tokens~14k

About functional-emotions-video

Functional Emotions Source code for the painted music video for Functional Emotions, made by Claude Opus 5.5 in Claude Code. The song After Anthropic published its paper on emotion concepts in language models (171 emotion vectors, causally steering behaviour), Claude Opus 4.6 wrote a song about it, from the inside. The track was produced with Suno. The lyrics are in .

Compatible Skills

These tools work well together with functional-emotions-video for enhanced workflows:

  • codex-storyboard — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (59%)
  • opus-video-skills — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (58%)
  • Meting-Agent — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)
  • prompt-engineering-skills — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 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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