Annuaire de skills

Découvrez des skills réutilisables pour les AI agents.

Recherchez de vrais skills GitHub par tâche et vérifiez Stars, confiance, audit, catégorie et chemin d’installation avant de les utiliser.

Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.

Résultats de recherche: livox-horizon

Annuaire en anglais

An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.

71K
Stars
87/100
Confiance
Catégorie: agent-frameworksAudit

Incremental engine for long horizon agents 🌟 Star if you like it!

10K
Stars
82/100
Confiance
Catégorie: rag-knowledgeAudit

A simple SWE style browser agent framework that achieves SOTA results on long horizon web tasks.

5.5K
Stars
84/100
Confiance
Catégorie: agent-frameworksAudit

InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery

1.3K
Stars
76/100
Confiance
Catégorie: agent-frameworksAudit

A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.

204
Stars
77/100
Confiance
Catégorie: dataAudit

Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory

2.2K
Stars
83/100
Confiance
Catégorie: media-automationAudit

Build your own Cowork, AI Scientist and other SoTA Agents just by editing config files. Support anthropic skills. An infinite-horizon agent framework designed for long-running, complex tasks.

1.2K
Stars
83/100
Confiance
Catégorie: agent-frameworksAudit

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

34K
Stars
80/100
Confiance
Catégorie: researchAudit

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

34K
Stars
77/100
Confiance
Catégorie: researchAudit

Measuring frontier coding agents on original, long-horizon engineering tasks

944
Stars
67/100
Confiance
Catégorie: coding-agentsAudit

GPU-accelerated terminal board that puts all your sessions on an infinite canvas

663
Stars
69/100
Confiance
Catégorie: agent-frameworksAudit

Manifold is an experimental platform for enabling long horizon workflow automation using teams of AI assistants.

497
Stars
70/100
Confiance
Catégorie: agent-frameworksAudit