rml
Skill1 starsChanged 5 months agoNo licenceView on GitHub
Recursive Learning Models (RLM) for deep exploration of context space. Analyzes PRefLexOR, Mixture-of-Recursions, Vertical LoRA, Graph-PReFLexOR, and related frameworks to enable iterative reasoning refinement, multi-agent self-correction, preference-based optimization with thinking tokens, adaptive token-level computation, graph-based symbolic reasoning, and recursive state updates for exploratory optimization in materials science, scientific discovery, complex problem solving, agentic AI thinking, knowledge expansion through dynamic graph construction, transfer learning across domains, stability-certified control systems, time series forecasting refinement, medical image segmentation improvement, and multi-step ahead prediction with iterative feedback loops.
In this repository51 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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