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Es werden 40 von 900 gesammelten Skills angezeigt.
You MUST use this whenever you build, change or review user interface code, including small UI tweaks and when the user is in a hurry: pages, components, forms, lists, tables, modals, navigation, layout or styling in React, Next.js, Vue, Svelte, Astro or…
Quellsprache: Englisch
Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks. Use when the user wants to deploy, host, publish, or set up their application on Render's cloud platform.
Quellsprache: Englisch
Scans a codebase and produces a quantified technical debt report with a prioritized remediation plan. Analyzes dead code, TODO/FIXME/HACK markers, dependency staleness, complexity hotspots, code duplication signals, test coverage gaps, unused exports, and…
Quellsprache: Englisch
Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.
Quellsprache: Englisch
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or…
Quellsprache: Englisch
Make an agent's database access provably read-only. Use when an agent runs caller-supplied SQL against a production/ERP/analytics database (a "query" MCP tool, text-to-SQL, an admin console), or when reviewing DB-access code for…
Quellsprache: Englisch
Score DeFi liquidity pools before providing liquidity. Returns a 0-100 pool score and an Enter/Hold/Exit/Reduce/Avoid verdict with calibrated confidence for ~68,800 Solana pools and 575 EVM pools, plus a public miss-inclusive track record. Use when asked…
Quellsprache: Englisch
You MUST use this before writing or changing any production code, including one-line fixes and when the user is in a hurry: a new feature, a bug fix, a refactor, a behavior change. Write the failing test first, run it and watch it fail for the right reason,…
Quellsprache: Englisch
Use for the 5 Whys, or when the user wants the root cause of a failure: "why did this happen?", "this keeps breaking", "write the postmortem", "find the real cause". Asks why repeatedly with evidence at each step, then sets countermeasures. Skip for one-off…
Quellsprache: Englisch
Use for a pre-mortem, or before committing to a plan, launch or migration: "what could go wrong?", "stress test this plan", "how might this fail?", "risks before we ship". Assumes failure, lists causes, ranks them and sets mitigations. Skip for explaining a…
Quellsprache: Englisch
Use when the user describes a problem, decision or stuck situation but names no method: "how should I approach this?", "help me think this through", "we can't decide", "where do I start?". Picks the best-fit thinking method and runs it. Skip for plain…
Quellsprache: Englisch
Use for tradeoff analysis, or when the user must pick between concrete options: "A or B?", "which library should we use?", "build vs buy", "compare these approaches". Scores options on weighted criteria, tests sensitivity and reversibility. Skip for open…
Quellsprache: Englisch
Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code. Use when user says "chisle mode", "activate chisle", "chislify", "be efficient", "be minimal", "no fluff", "yagni", or invokes /chisle. Deactivate: "stop chisle" / "normal mode".
Quellsprache: Englisch
Find open US healthcare jobs (nursing, CNA, allied health, therapy, imaging, pharmacy, physicians and more) and the hourly pay employers post, using CareJobs.Now's free MCP server or its public JSON endpoints. Use when someone asks for healthcare or nursing…
Quellsprache: Englisch
You MUST use this whenever something is broken, before proposing or making any fix, including quick fixes and when the user is in a hurry: a bug, a failing or red test, a build or CI failure, a crash, a performance problem, unexpected behavior. Finds the root…
Quellsprache: Englisch
You MUST use this when asked to review code: a pull request, a branch, a commit, staged or uncommitted changes, or "check this before I merge". Scopes the review to the diff, reads the surrounding code, hunts for real bugs (correctness, security, data loss,…
Quellsprache: Englisch
You MUST use this before any creative or build work: creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a website, a talk, a business). Finds out what the user actually wants…
Quellsprache: Englisch
Open other Claude Code sessions in Rex terminal panes or tabs and drive them: launch claude in a directory, answer the workspace trust dialog, send prompts, wait for each turn by its reported status (working, done, blocked on a permission prompt), read the…
Quellsprache: Englisch
Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.
Quellsprache: Englisch
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring…
Quellsprache: Englisch
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots,…
Quellsprache: Englisch
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval,…
Quellsprache: Englisch
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for…
Quellsprache: Englisch
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing,…
Quellsprache: Englisch
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace…
Quellsprache: Englisch
Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention
Quellsprache: Englisch
Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert…
Quellsprache: Englisch
Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2
Quellsprache: Englisch
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best…
Quellsprache: Englisch
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines…
Quellsprache: Englisch
Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature…
Quellsprache: Englisch
Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient…
Quellsprache: Englisch
Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly…
Quellsprache: Englisch
Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers…
Quellsprache: Englisch
Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity…
Quellsprache: Englisch
Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute.…
Quellsprache: Englisch
Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard…
Quellsprache: Englisch
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace,…
Quellsprache: Englisch
Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with…
Quellsprache: Englisch
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Quellsprache: Englisch
README-Quelldatei: README.md
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