future-tokens
Every AI output has structural blind spots determined by the generation process itself. Future Tokens operations are named, composable instruments that target specific blind spots. They surface new information on every pass because expanding the output changes the blind spot geometry.
npx skills add majiayu000/claude-skill-registry --skill future-tokens --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Future Tokens: Corrective Instruments for AI Reasoning Every AI output has structural blind spots. Coherence optimization suppresses gaps. Token-level generation locks in frames before alternatives are considered. Confidence distributes smoothly over claims that deserve scrutiny in different places. These aren't random errors — they're predictable artifacts of how generation works. Future Tokens operations are named, composable instruments that target specific blind spot types. Each one reliably surfaces information that the generation process systematically omits, because the blind spots are structural, not random. And they're generative — every pass changes the consideration space, shifting the blind spot geometry so the next pass finds new material. Part of the [FUTURE TOKENS](https://jordanmrubin.substack.com/p/future-tokens) project. This collection is compatible with both Claude and Codex workflows. ## When to use If you just produced an output, it has predictable gaps. Match what you built to the operation that catches what it missed. | you just built… | it probably missed… | run this | |------------------------------------|-------------------------------------------------
- When to use
- Key properties
- Core Skills
- Using These Skills
- Philosophy
- Repository Structure
- Contributing
What does the future-tokens skill do?
Every AI output has structural blind spots determined by the generation process itself. Future Tokens operations are named, composable instruments that target specific blind spots. They surface new information on every pass because expanding the output changes the blind spot geometry.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill future-tokens --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.