by jordanrubin · Agent Tool · ★ 65
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
/plugin marketplace add jordanrubin/FUTURE_TOKENS
/plugin install future-tokens-skills@future-tokensTaken from the project's README on GitHub. Check the security audit before running it.
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.
| Stars | 65 |
| Forks | 4 |
| Language | Shell |
| Category | Agent Tool |
| Quality Score | 68/100 |
| Last Updated | 2026-02-19 |
| Created | 2025-07-11 |
| Platforms | claude-code, cli |
| Est. Tokens | ~13k |
Future Tokens Every AI output has structural blind spots. Coherence optimization suppresses gaps. Token-level generation locks in frames before alternatives are considered. Future Tokens operations are named, composable instruments that target specific blind spot types—surfacing information that the generation process systematically omits.
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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: