Browse published AI skills maintained by letta-ai. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
206Repository stars across indexed skills
39,577Repository forks
4,798Average repository stars per indexed skill
192Repository stars may repeat across skills from the same repository.
Guide for using the Letta Conversations API to manage isolated message threads on agents. Use when building multi-user chat applications, session management, or any scenario requiring separate conversation cont...
Guidance for setting up HuggingFace model inference services with Flask APIs. This skill applies when downloading HuggingFace models, creating inference endpoints, or building ML model serving APIs. Use for tas...
Guidance for counting tokens in datasets, particularly from HuggingFace or similar sources. This skill should be used when tasks involve counting tokens in datasets, understanding dataset schemas, filtering by...
Guide for building pMARS (Portable Memory Array Redcode Simulator) and similar software from Debian/Ubuntu source packages. Use this skill when tasks involve enabling source repositories, downloading distributi...
Decode and interpret text content from G-code files by analyzing toolpath geometry and coordinate patterns. This skill should be used when extracting text, letters, or symbols that are encoded as movement comma...
Guidance for extracting text-based game commands, moves, or inputs from video recordings using OCR and frame analysis. This skill applies when extracting user inputs from screen recordings of text-based games (...
This skill provides guidance for reverse engineering compiled binaries to produce equivalent source code. It applies when tasks require analyzing executables, extracting algorithms and constants, and recreating...
Guide for performing Markov Chain Monte Carlo (MCMC) sampling using RStan or PyStan. This skill should be used when implementing Bayesian statistical models, fitting hierarchical models, working with Stan model...
Guidance for Bayesian Network DAG structure recovery, parameter learning, and causal intervention tasks. This skill should be used when tasks involve recovering DAG structure from observational data, learning B...
This skill should be used when reconstructing PyTorch models from weight files (state dictionaries), checkpoint files, or partial model artifacts. It applies when the agent needs to infer model architecture fro...
Guidance for reverse engineering graphics rendering programs (ray tracers, path tracers) from binary executables. This skill should be used when tasked with recreating a program that generates images through ra...
Meta-skill for recognizing learnings, validating improvements, and contributing back to the collective knowledge base. Use when agents discover better patterns, find gaps in existing skills, or want to improve...
Skill for handling PR code reviews. Use when triggered by a PR review comment, review request, or when asked to review code changes. Provides workflow for reading review comments, understanding feedback, and it...
Skill for GitHub Actions CI environment. Use when running inside a GitHub Actions workflow to update tracking comments, commit code, and interact with GitHub.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.