bio-epitranscriptomics-m6anet-analysis：Nanopore direct RNA m6A detection ，支持 m6Anet 深度学习。
FreedomIntelligence/OpenClaw-Medical-Skills查看
训练与评测
GE
Get Available Resources
维护者 K-Dense Inc. · 最近更新 2026年4月1日
Get Available Resources：检测 available computational resources 、 generate strategic recommendations ，用于 scientific computing tasks。 This skill automatically identifies CPU capabilities，GPU availability (NVIDIA CUDA，AMD ROCm，Apple Silicon Metal)，memory constraints，、 disk space to help make informed decisions about computational approaches。
原始来源
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/get-available-resources
- 维护者
- K-Dense Inc.
- 许可
- MIT license
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- 检测 available computational resources 、 generate strategic recommendations ，用于 scientific computing tasks. This skill automatically identifies CPU capabilities，GPU availability (NVIDIA CUDA，AMD ROCm，Apple Silicon Metal)，memory constraints，、 disk space to help make informed decisions about computational approaches。
- 支持 open('.claude_resources.json'，'r') as f：resources = json.load(f)。
原始文档
SKILL.md 摘录
When to Use This Skill
Use this skill proactively before any computationally intensive task:
- Before data analysis: Determine if datasets can be loaded into memory or require out-of-core processing
- Before model training: Check if GPU acceleration is available and which backend to use
- Before parallel processing: Identify optimal number of workers for joblib, multiprocessing, or Dask
- Before large file operations: Verify sufficient disk space and appropriate storage strategies
- At project initialization: Understand baseline capabilities for making architectural decisions
Example scenarios:
- "Help me analyze this 50GB genomics dataset" → Use this skill first to determine if Dask/Zarr are needed
- "Train a neural network on this data" → Use this skill to detect available GPUs and backends
- "Process 10,000 files in parallel" → Use this skill to determine optimal worker count
- "Run a computationally intensive simulation" → Use this skill to understand resource constraints
Resource Detection
The skill runs scripts/detect_resources.py to automatically detect:
-
CPU Information
- Physical and logical core counts
- Processor architecture and model
- CPU frequency information
-
GPU Information
- NVIDIA GPUs: Detects via nvidia-smi, reports VRAM, driver version, compute capability
- AMD GPUs: Detects via rocm-smi
- Apple Silicon: Detects M1/M2/M3/M4 chips with Metal support and unified memory
-
Memory Information
- Total and available RAM
- Current memory usage percentage
- Swap space availability
-
Disk Space Information
- Total and available disk space for working directory
- Current usage percentage
-
Operating System Information
- OS type (macOS, Linux, Windows)
- OS version and release
- Python version
Output Format
The skill generates a .claude_resources.json file in the current working directory containing:
适用场景
- **Before 数据分析**：Determine if 数据集s can be loaded into memory 或 require out-of-core processing。
- **Before model training**：Check if GPU acceleration is available 、 which backend to use。
- **Before parallel processing**：Identify optimal number of workers ，用于 joblib，multiprocessing，或 Dask。
- **Before large file operations**：Verify sufficient disk space 、 appropriate storage strategies。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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