ML Ops
Machine learning operations
sec-business-desc-analysis
by OctagonAI
Extract and analyze business descriptions and competitive landscape from SEC filings using Octagon MCP. Use when researching company business models, market positioning, competitive advantages, industry dynamics, and strategic focus areas from Item 1 disclosures.
industry-pe-ratios
by OctagonAI
Retrieve industry-specific P/E ratios using Octagon MCP. Use when comparing company valuations to specific industry peers, analyzing sub-sector valuations, and understanding niche market valuations beyond broad sector averages.
earnings-analyst-questions
by OctagonAI
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.
abductive-repl
by plurigrid
' Hypothesis-Test Loops via REPL for Exploratory Abductive Inference'
earnings-product-pipeline
by OctagonAI
Extract product development and pipeline updates from earnings calls, including clinical trial progress, regulatory submissions, and launch timelines.
owasp-ai-testing
by mastepanoski
AI trustworthiness testing using OWASP AI Testing Guide v1. Execute 44 test cases across 4 layers (Application, Model, Infrastructure, Data) with practical payloads and remediation.
business-competitor-analysis
by kenneth-liao
Perform comprehensive competitor analysis for any business. Produces an executive-summary markdown report with target customer profile, market positioning, pricing/business model, product features, funding/company size, SWOT analysis, and competitive matrix. All findings are data-grounded. Use when the user asks to analyze competitors, understand competitive landscape, compare a business to alternatives, or perform market research.
nanobanana
by kenneth-liao
AI image generation and editing using Google Gemini models (Nano Banana). Use when the user asks to generate an image, create an image, edit an image, or references "nano banana", "nanobanana", or "gemini image". Supports text-to-image, image editing, multi-image references, and 1K/2K/4K resolution.
plan
by jh941213
복잡한 작업 전 계획 수립. Plan 모드에서 사용하거나 "계획", "플랜", "어떻게 구현" 등의 키워드에 자동 활성화.
compact-guide
by jh941213
컨텍스트 관리 가이드. "컨텍스트", "토큰", "compact" 키워드에 활성화.
git
by maragudk
Guide for using git according to my preferences. Use it when you're asked to commit something.
deep-learning-pytorch
by Mindrally
Expert guidance for deep learning, transformers, diffusion models, and LLM development with PyTorch, Transformers, Diffusers, and Gradio.
jenkins
by BagelHole
Create and manage Jenkins CI/CD pipelines, configure agents, manage plugins, and automate builds. Use when working with Jenkins servers, creating Jenkinsfiles, or setting up build automation for enterprise environments.
implementing-mlops
by ancoleman
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
model-hierarchy
by zscole
Cost-optimize AI agent operations by routing tasks to appropriate models based on complexity. Use this skill when: (1) deciding which model to use for a task, (2) spawning sub-agents, (3) considering cost efficiency, (4) the current model feels like overkill for the task. Triggers: "model routing", "cost optimization", "which model", "too expensive", "spawn agent".
r3f-loaders
by EnzeD
React Three Fiber asset loading - useGLTF, useLoader, Suspense patterns, preloading. Use when loading 3D models, textures, HDR environments, or managing loading states.
ai-engineer
by tao12345666333
Expert knowledge in AI/ML development, model deployment, and MLOps practices
feature-pipeline
by notedit
Execute implementation tasks from design documents using markdown checkboxes. Use when (1) implementing features from feature-analyzer output, (2) resuming interrupted work, (3) batch executing tasks. Triggers on 'start implementation', 'run tasks', 'resume'.
model-serving
by ancoleman
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
domain-driven-design
by joaquimscosta
Expert guidance for Domain-Driven Design architecture and implementation. Use when designing complex business systems, defining bounded contexts, structuring domain models, choosing between modular monolith vs microservices, implementing aggregates/entities/value objects, or when users mention "DDD", "domain-driven design", "bounded context", "aggregate", "domain model", "ubiquitous language", "event storming", "context mapping", "domain events", "anemic domain model", strategic design, tactical patterns, or domain modeling. Helps make architectural decisions, identify subdomains, design aggregates, and avoid common DDD pitfalls.
aiconfig-update
by launchdarkly
Update, archive, and delete LaunchDarkly AI Configs and their variations. Use when you need to modify config properties, change model parameters, update instructions or messages, archive unused configs, or permanently remove them.
fiftyone-dataset-inference
by voxel51
Run ML model inference (YOLO, YOLOv8, CLIP, SAM, Detectron2, etc.) on FiftyOne datasets. Use when running models, applying detection, classification, segmentation, embeddings, or any model prediction task. Also use for end-to-end workflows that include importing data then running inference.
deep-learning
by Mindrally
Comprehensive deep learning guidelines for neural network development, training, and optimization.
start-feature
by leeovery
"Start a new feature through the full pipeline. Gathers context via structured interview, creates a discussion, then bridges to continue-feature for specification, planning, and implementation."