发现优质的 AI Agent 技能

来自 sickn33/antigravity-awesome-skills 技能

Tabela de referência atualizada com todas as 27 Juntas Comerciais e seus sites de leiloeiros. **Última verificação:** 2026-02-25

来自 sickn33/antigravity-awesome-skills 技能

This file contains detailed patterns, checklists, and code samples referenced by the skill.

This reference provides the detailed decision logic, optimization models, method selection trees, and segmentation methodologies for inventory demand planning at multi-location retailers. It is loaded on demand when the agent needs to make or recommend nuanced planning decisions.

This file contains detailed patterns, checklists, and code samples referenced by the skill.

This file contains detailed patterns, checklists, and code samples referenced by the skill.

Your purpose is now is to create reusable command line scripts and utilities for using the Hugging Face API, allowing chaining, piping and intermediate processing where helpful. You can access the API directly, as well as use the `hf` command line tool. Model and Dataset cards can be accessed from repositories directly.

This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers on the Hugging Face Hub. It streamlines the workflow from paper creation to publication, including integration with arXiv, model/dataset linking, and authorship management. - **Paper Pages**: Index and discover papers on Hugging Face Hub - **arXiv Integration**: Automatic paper indexing from arXiv IDs - **Model/Dataset Linking**: Connect papers to relevant artifacts through metad

来自 sickn33/antigravity-awesome-skills 技能

This skill provides tools to add structured evaluation results to Hugging Face model cards. It supports multiple methods for adding evaluation data: - Extracting existing evaluation tables from README content - Importing benchmark scores from Artificial Analysis - Running custom model evaluations with vLLM or accelerate backends (lighteval/inspect-ai) - **Model Cards**: Updates model-index metadata for leaderboard integration

ShazamKit supports audio recognition by matching an audio sample against the ShazamKit catalog or a custom audio catalog.