thinking-orbs: Dotted thought-orb loading indicators for AI & agent UIs, 9 tuned types, two sizes, auto dark/light

by Jakubantalik · Agent Tool · ★ 3.9k

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

How to install thinking-orbs

npm install thinking-orbs

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 73/100

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.

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Quick Facts

Stars3,930
Forks314
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score73/100
Open Issues23
Last Updated2026-08-16
Created2026-07-21
Platformsnode
Est. Tokens~14k

About thinking-orbs

thinking-orbs Dotted thought-orb loading indicators for AI & agent UIs. Nine hand-tuned animated states, each shipped at two purpose-tuned sizes, rendered on a plain 2D canvas — no WebGL, no filters, works identically in Chrome, Safari and Firefox.

Compatible Skills

These tools work well together with thinking-orbs for enhanced workflows:

  • adhd — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • Flowtrace — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (55%)
  • darknet-mcp-server — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (55%)

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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:

View on GitHub → Browse Agent Tool tools