distributed-training
Multi-GPU and distributed training patterns with PyTorch DDP. Use when scaling training across GPUs.
Multi-GPU and distributed training patterns with PyTorch DDP. Use when scaling training across GPUs.
Best practices for building robust PyTorch training loops. Use when generating or reviewing ML training code.
Systematic literature review methodology including search strategy, screening, and synthesis. Use when conducting literature reviews or writing background sections.
Academic manuscript writing with IMRAD structure, citation formatting, and reporting guidelines. Use when drafting or revising research papers.
Statistical test selection, assumption checking, and APA-formatted reporting. Use when analyzing experimental results or writing results sections.
Structured methodology for comprehensive literature review following PRISMA guidelines. Use during literature search and screening stages.
Best practices for image classification tasks. Use when working on CIFAR, ImageNet, or other classification benchmarks.
Bioinformatics with Biopython for sequence manipulation, file parsing, BLAST, and phylogenetics. Use when working with DNA/RNA/protein sequences or biological databases.
Computational chemistry with RDKit for molecular analysis, descriptors, fingerprints, and substructure search. Use when working with SMILES, drug discovery, or cheminformatics tasks.
Best practices for object detection tasks. Use when working on COCO, VOC, or detection architectures like YOLO and DETR.
Best practices for designing reproducible ML experiments. Use when planning ablations, baselines, or controlled experiments.
Run the ResearchClaw autonomous research pipeline from a topic, config, and output directory.
Implementing custom elements using GPUI's low-level Element API (vs. high-level Render/RenderOnce APIs). Use when you need maximum control over layout, prepaint, and paint phases for complex, performance-critical custom UI components that cannot be achieved with Render/RenderOnce traits.
GPUI Component project style guide based on gpui-component code patterns. Use when writing new components, reviewing code, or ensuring consistency with existing gpui-component implementations. Covers component structure, trait implementations, naming conventions, and API patterns observed in the actual codebase.
Use this skill when you need to execute SQL against the MoviePilot database. This skill guides you through connecting to the database and executing SQL statements. The database type (SQLite or PostgreSQL) and connection details are provided in the system prompt <system_info>. Applicable scenarios include: 1) The user asks about data statistics, counts, or aggregations that existing tools don't cover; 2) The user wants to inspect, modify, or fix raw database records; 3) The user asks to clean up data, update records, or perform database maintenance; 4) The user asks questions like "how many downloads", "show me site stats", "delete old records", etc.
Use this skill when you need to retry failed file transfers/organizations. Given one or more failed transfer history record IDs, this skill guides you through querying the failure details, deleting the old records, and re-identifying and re-organizing the files. Supports batch processing of multiple files from the same media (e.g., multiple episodes of a TV show). This skill is automatically triggered when the system detects transfer failures and the AI agent retry feature is enabled.
Use this skill when a user provides a torrent name or file name and wants to fix recognition issues, or asks to add/manage custom identifiers (自定义识别词). This skill generates identifier rules based on the WordsMatcher preprocessing logic, checks for duplicates against existing rules, and saves them via MCP tools. Applicable scenarios include: 1) A torrent or file name is incorrectly recognized (wrong title, season, episode, etc.); 2) The user wants to block unwanted keywords from torrent names; 3) The user needs episode offset rules for series with non-standard numbering; 4) The user wants to force recognition of a specific media by TMDB/Douban ID.
Download files in Chrome on Windows and macOS. Handles triggering downloads, detecting and resolving popups, verifying completion, and locating files.
Guide for creating effective skills. Use when users want to create a new skill (or update an existing skill) that extends the AI's capabilities with specialized knowledge, workflows, or tool integrations.
Research topics on the web, gather information from multiple sources, and summarize findings.