ML Ops
Machine learning operations
performance-scaling
by bejranonda
Cross-model performance optimization and scaling configurations for autonomous agents
view-refactor
by patrickserrano
Refactor SwiftUI view files for consistent structure, dependency injection, and Observation usage. Use when asked to clean up a SwiftUI view's layout, handle view models safely, or standardize how dependencies are initialized and passed.
python-peewee
by narumiruna
Patterns for using Peewee ORM with DatabaseProxy and scoped connections/transactions. Use when setting up DatabaseProxy, managing connection_context/atomic blocks, or writing tests with SQLite.
tinygrad
by av
Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.
writing-clearly-and-concisely
by sebnow
"Use when writing documentation, commit messages, error text, explanations, reports, or summaries. Applies Strunk's principles for clear, vigorous prose. Triggers: writing human-readable content, verbose text, unclear explanations."
whisper-test
by TrevorS
Transcribe WAV audio files using OpenAI Whisper for intelligibility testing. Triggers on: "transcribe audio", "whisper test", "test audio output", "is the audio intelligible", "check speech quality", "run whisper", "speech to text test", "check if audio sounds right"
ml-ablation-design
by dongzhuoyao
Use when designing ablation studies to compare model components, loss functions, or architectural choices. Covers synthetic data experiments, variant loops, production metrics, and W&B grouping. Triggers: "ablation", "ablation study", "variant comparison", "controlled experiment", "synthetic data experiment"
fail-fast-ml-engineering
by dongzhuoyao
Use when designing ML training pipelines, data loaders, or inference systems. Enforces engineering discipline — no silent fallbacks, explicit errors on critical paths, config as single source of truth. Triggers: "silent failure", "fallback", "preflight", "assertion", "error handling", "fail fast", "config truth"
wandb-experiment-tracking
by dongzhuoyao
Use when integrating W&B experiment tracking into ML training pipelines, including logging strategy, run configuration, and online/offline mode management. Triggers: "W&B", "wandb", "weights and biases", "experiment logging", "wandb.log", "wandb.init", "training dashboard"
prompt-engineering
by lv416e
"Use when designing, testing, or deploying LLM prompts for applications - systematic prompt design methodology (pattern selection, structured output, evaluation, versioning) ensuring every prompt is tested against ground truth before production LLMプロンプトの設計、テスト、デプロイ時に使用 - 体系的なプロンプト設計手法（パターン選択、構造化出力、評価、バージョン管理）により、すべてのプロンプトが本番前にグランドトゥルースに対してテスト済みであることを保証"
3d-web-experience
by ranbot-ai
Expert in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing ...
model-first-reasoning
by petekp
Apply Model-First Reasoning (MFR) to code generation tasks. Use when the user requests "model-first", "MFR", "formal modeling before coding", "model then implement", or when tasks involve complex logic, state machines, constraint systems, or any implementation requiring formal correctness guarantees. Enforces strict separation between modeling and implementation phases.
advanced-evaluation
by xfstudio
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
account-executive
by ncklrs
Expert full-cycle enterprise sales strategist for B2B SaaS. Use when planning sales strategy, pipeline management, deal progression, account planning, competitive displacement, or territory optimization. Covers multi-threading, executive engagement, champion development, buying committee navigation, and complex deal orchestration. Use for enterprise selling, account expansion, land-and-expand, and quota attainment.
event-marketer
by ncklrs
Expert event marketing guidance for conferences, webinars, and field programs. Use when planning event strategy, creating booth presence, running webinars, producing virtual events, writing event promotion copy, preparing speakers, designing follow-up sequences, or measuring event ROI. Use for conference sponsorships, trade shows, user conferences, meetups, field marketing, and hybrid events.
sales-enablement
by ncklrs
Expert sales enablement strategist for building high-performing sales teams. Use when designing sales training programs, onboarding and ramp plans, sales playbooks, coaching frameworks, certification programs, or competitive intelligence distribution. Covers content strategy, tool adoption, performance measurement, and continuous learning systems. Use for building sales academies, creating enablement content, and optimizing sales productivity.
agentic-development
by Exploration-labs
Conversational guidance for building software with AI agents, covering workflows, tool selection, prompt strategies, parallel agent management, and best practices based on real-world high-volume agentic development experience. Use this skill when users ask about setting up agentic workflows, choosing models, optimizing prompts, managing parallel agents, or improving agent output quality.
competitor-analysis
by assimovt
Analyze competitive landscape with feature matrices, positioning maps, and strategic gap analysis. Use when asked to analyze competitors, map the competitive landscape, find differentiation, or evaluate alternatives to a product.
ML/AI Skills Conversion Project
by 404kidwiz
Follow the existing patterns to implement these skills.
model-council
by michaelboeding
This skill should be used when the user asks for "model council", "multi-model", "compare models", "ask multiple AIs", "consensus across models", "run on different models", or wants to get solutions from multiple AI providers (Claude, GPT, Gemini, Grok) and compare results. Orchestrates parallel execution across AI models/CLIs and synthesizes the best answer.
gpu-training-acceleration
by dongzhuoyao
Use when optimizing PyTorch training speed or memory on CUDA GPUs — global flags, torch.compile, fused optimizers, mixed precision, gradient checkpointing, kernel fusion, memory layout, or latent-space training. Applies to any PyTorch training workload. Triggers: "torch.compile", "TF32", "fused optimizer", "mixed precision", "bf16", "fp16", "gradient checkpointing", "Triton kernel", "CUDA flags", "GPU slow", "GPU memory"
financial-modeling
by mfwarren
Production-ready entrepreneurship skills for Claude Code — marketing, sales, operations, finance, and leadership. 24 skills built by a founder, for founders.
unit-economics
by mfwarren
Production-ready entrepreneurship skills for Claude Code — marketing, sales, operations, finance, and leadership. 24 skills built by a founder, for founders.
marginaleffects
by vincentarelbundock
Manual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.