GitHub
object
Interactable things in the world — the atoms of adventure
☆ 15Voir le skill
Skills IA Contenu et médias
Découvrez les skills Contenu et médias, comparez leurs dépôts et consultez leurs instructions.
Catégories: Contenu et médias
Contenu et médias Effacer les filtres
Explorer
GitHub
bartender
Generic bartending capabilities — pour drinks, manage tabs, know regulars
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GitHub
memory-palace
Spatial organization of knowledge in navigable directories
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GitHub
skill-snitch
Security auditing for MOOLLM skills - static analysis and runtime surveillance
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GitHub
markdown
Plain text formatting that's readable raw AND rendered
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GitHub
society-of-mind
Intelligence emerges from many simple agents (Minsky)
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GitHub
simulator-effect
Implication beats simulation — imagination renders (Will Wright)
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GitHub
probability
Motto: The LLM is the dice. It narrates the outcome.
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GitHub
party
Companions and group dynamics — you're never alone
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GitHub
advertisement
Objects announce what they can do — The Sims style
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GitHub
constructionism
Educational philosophy — learn by building inspectable things
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GitHub
budtender
Cannabis-specialized bartender — strains, terpenes, edibles, rolling
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GitHub
naming
Big-endian file naming as semantic binding
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GitHub
coherence-engine
The LLM as consistency maintainer and orchestrator
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GitHub
debugging
Systematic bug investigation with hypothesis tracking
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GitHub
storytelling-tools
Build narrative capture and sharing into the system.
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GitHub
evaluator
Independent assessment without debate context — adversarial loop prevents gaming
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GitHub
visualizer
I see what you describe. Let me show it to others.
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GitHub
leela-ai
Manufacturing Intelligence — Leela AI applies MOOLLM to industry
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GitHub
action-queue
Sims-inspired task scheduling — queue actions, execute in order
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GitHub
self-repair
Missing state triggers repair, not failure.
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GitHub
skill
A skill is documentation that learned to do things.
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GitHub
research-notebook
Structured research with sources, findings, and decisions.
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GitHub
code-review
Systematic code analysis with evidence collection
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Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.