Example skill loaded from resources_discover
原文语言:英语
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SkillsMP 已收集 VectorSpaceLab/AREX-Skill 中的 5,368 个 Skill。打开任一 Skill 可查看来源和详情。
复制这段 Prompt,发给你正在使用的 AI 助手。
请帮我从这个仓库安装 Agent Skills:https://github.com/VectorSpaceLab/AREX-Skill
先检查来源、SKILL.md 和配套文件,列出可安装的 Skill 让我选择。得到选择后,将选中的完整 Skill 目录安装到当前项目,并确认所需文件已就位。已展示 40 / 5,368 个已收集 Skill。
Example skill loaded from resources_discover
原文语言:英语
Creates reusable Agent Skills from an AI research paper using the Paper2Skills Distiller workflow. Use in Creator mode when the user provides a paper PDF, paper URL, arXiv id, paper title, or paper/repo pair, or asks to convert a scientific paper into skills…
原文语言:英语
Creates a repo-specific operating Agent Skill for DisCo Researcher from a local repository by inspecting source files and an installed or auto-prepared, backend-aware Python package environment. Use when the user asks to create a skill for a repo, generate…
原文语言:英语
Extends an existing repository-specific Agent Skill with new capabilities, deeper coverage, troubleshooting, scripts, and usability tests. Use when the user asks to expand, improve, deepen, or add coverage to an already implemented skill instead of creating a…
原文语言:英语
Use this skill when the user asks to export DisCo's managed repository skills and repo-skills-router into another agent tool such as Codex under ~/.agents/skills, Claude Code under ~/.claude/skills, or a project-local agent directory. Handles canonical source…
原文语言:英语
Refreshes an existing repository-specific Agent Skill after the source repository changed. Use when the user says repo code, APIs, docs, examples, configs, dependencies, or behavior changed and an old skill may now be stale, outdated, inconsistent with…
原文语言:英语
Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality,…
原文语言:英语
Verifies a generated or refreshed repo-specific Agent Skill by creating assertion-backed usability test cases, running content-level self-refine, checking backend-classified native repo examples/tests against the prepared CPU/GPU environment plan, enforcing…
原文语言:英语
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
原文语言:英语
Prepare raw videos and annotations for the 3D-ResNets-PyTorch dataset loaders.
原文语言:英语
Routes training, fine-tuning, validation, checkpoint, and inference workflows for 3D ResNets PyTorch.
原文语言:英语
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
原文语言:英语
Operate the optional 3DDFA C++ OpenCV DNN port, checkpoint-to-ONNX export, weight placement, build/run expectations, and C++ troubleshooting.
原文语言:英语
Reconstruct 3DMM vertices, serialize mesh outputs, and manage 3DDFA rendering helpers.
原文语言:英语
Operate 3DDFA Python image and video inference for landmarks, dense vertices, meshes, pose boxes, depth, PNCC, and PAF outputs.
原文语言:英语
Routes 3DDFA training recipes, loss selection, checkpoint resume, dataset layout, and benchmark evaluation.
原文语言:英语
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
原文语言:英语
Use 3DDFA_V2 ONNX Runtime acceleration and CPU latency or speed benchmark workflows.
原文语言:英语
Prepare 3DDFA_V2 runtime assets and native extension builds before demos or benchmarks.
原文语言:英语
Run 3DDFA_V2 still-image alignment, rendering, pose, texture, and mesh export workflows.
原文语言:英语
Run 3DDFA_V2 video, smoothing, and manual webcam tracking workflows.
原文语言:英语
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
原文语言:英语
Routes KITTI and nuScenes data-layout, detection-conversion, and schema-validation work for AB3DMOT inputs.
原文语言:英语
Evaluate, threshold, combine, and visualize AB3DMOT KITTI and nuScenes tracking results.
原文语言:英语
Run AB3DMOT tracking safely and use the core AB3DMOT tracker APIs for KITTI and nuScenes 3D MOT workflows.
原文语言:英语
Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
原文语言:英语
Use Accelerate big-model inference utilities for meta initialization, device-map planning, checkpoint dispatch, CPU/disk offload, hooks, pipeline inference, and memory sizing without triggering downloads or heavyweight runs.
原文语言:英语
Save and resume Accelerate training state, register checkpoint hooks and custom state, log safely across processes, use experiment trackers, profile runs, and clean up memory.
原文语言:英语
Use this sub-skill when working with Hugging Face Accelerate configuration files and CLI commands, including accelerate config/default/update/env/launch/test/estimate-memory/merge-weights/to-fsdp2, launch command construction, multi-node and SLURM planning,…
原文语言:英语
Select, configure, and diagnose Accelerate distributed training backends including DeepSpeed, FSDP/FSDP2, Megatron-LM, torch native parallelism, TPU/XLA, FP8, quantization, compilation, Local SGD, and DDP communication hooks.
原文语言:英语
Migrate raw PyTorch training and evaluation loops to Hugging Face Accelerate using Accelerator, prepare(), backward(), gradient accumulation, dataloader behavior, gather/reduce, mixed precision, DDP kwargs, local SGD, communication hooks, and basic…
原文语言:英语
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
原文语言:英语
Build and debug Acme core dm_env loops, specs, wrappers, logging, counting, observers, and simple custom Actor/Learner components.
原文语言:英语
Select, configure, and adapt Acme JAX agents and JAX experiment workflows.
原文语言:英语
Use Acme adders, Reverb replay tables and datasets, offline data iterators, image augmentation, and replay shape troubleshooting.
原文语言:英语
Select, configure, debug, and adapt Acme TensorFlow/Sonnet agents, networks, savers, Launchpad examples, and TF losses.
原文语言:英语
Routes ACT++, ACT, Diffusion Policy, VINN, and MuJoCo simulation workflows for bimanual ALOHA episode data and imitation-learning tasks.
原文语言:英语
Routes ACT, CNNMLP, Diffusion Policy, and latent-model training or evaluation workflows for ACT++ checkpoints and datasets.
原文语言:英语
Routes simulated ALOHA episode generation, replay, visualization, mirroring, compression, and truncation workflows for ACT++ HDF5 data.
原文语言:英语
Routes VINN feature caching and non-interactive k-selection workflows for ACT++ BYOL/ResNet episode features.
原文语言:英语