ML Ops
Machine learning operations
summarize
by HKUDS
Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
ai-ethics-review
by mohitagw15856
"Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety, accountability, and societal impact with a risk tier score, pre-deployment checklist, and prioritised mitigations."
baoyu-image-gen
by JimLiu
AI image generation with OpenAI, Google, DashScope and Replicate APIs. Supports text-to-image, reference images, aspect ratios. Sequential by default; parallel generation available on request. Use when user asks to generate, create, or draw images.
competitive-analysis
by RefoundAI
Help users understand and respond to competition. Use when someone is positioning against competitors, evaluating market threats, running competitive war games, or deciding how much to focus on competitors versus customers.
pydantic-ai-testing
by existential-birds
Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.
change-management-plan
by mohitagw15856
"Create a structured change management plan for any organisational change. Use when asked to write a change management plan, manage a change initiative, plan a system rollout, or lead an organisational transformation. Produces a plan covering stakeholder analysis, impact assessment, communication strategy, and resistance management."
gentleman-bubbletea
by Gentleman-Programming
Bubbletea TUI patterns for Gentleman.Dots installer. Trigger: When editing Go files in installer/internal/tui/, working on TUI screens, or adding new UI features.
cobrapy
by jimmc414
"Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis."
aeon
by jimmc414
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
gentleman-installer
by Gentleman-Programming
Installation step patterns for Gentleman.Dots TUI installer. Trigger: When editing installer.go, adding installation steps, or modifying the installation flow.
domain-layer
by atopile
"Instructions for electronics-specific logic and build processes: netlists, PCBs, build steps, and exporters. Use when implementing or modifying build steps, exporters, PCB generation, or BOM/netlist output."
hugging-face-model-trainer
by huggingface
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
hugging-face-evaluation
by huggingface
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
hugging-face-paper-publisher
by huggingface
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
hf-mcp
by huggingface
Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.
domain-modeling
by windmill-labs
Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, or when another skill needs to maintain the domain model.
fal-audio
by fal-ai-community
Text-to-speech and speech-to-text using fal.ai audio models. Use when the user requests "Convert text to speech", "Transcribe audio", "Generate voice", "Speech to text", "TTS", "STT", or similar audio tasks.
deseq2-differential-expression
by jaechang-hits
"Differential expression analysis for bulk RNA-seq using R/Bioconductor DESeq2. Negative binomial GLM with empirical Bayes shrinkage, Wald and LRT tests, multi-factor designs, interaction terms, Salmon tximeta import, apeglm LFC shrinkage, MA/volcano/heatmap visualization. The R gold standard for DE analysis with native Bioconductor integration. Use pydeseq2-differential-expression for Python-based pipelines; use edgeR for TMM normalization."
cellpose-cell-segmentation
by jaechang-hits
"Deep learning cell and nucleus segmentation from fluorescence and brightfield microscopy images. Uses pre-trained models (cyto3, nuclei, tissuenet) and a generalist flow-based algorithm that segments cells without requiring retraining on new image types. Outputs label masks for downstream morphology measurement and tracking. Use scikit-image watershed for rule-based segmentation; use Cellpose when deep learning generalization across staining conditions is needed."
nnunet-segmentation
by jaechang-hits
"Train and deploy automated medical image segmentation models using nnU-Net's self-configuring framework that auto-selects optimal architecture, preprocessing, and training for any modality. Supports CT, MRI, microscopy, and ultrasound with 2D, 3D full-res, 3D low-res, and cascade configurations. Pipeline: convert dataset → plan and preprocess → train (5-fold cross-validation) → find best configuration → predict → ensemble. Use when classical segmentation fails and annotated training data is available."
napari-image-viewer
by jaechang-hits
"Interactive multi-dimensional image viewer for scientific microscopy data. Napari displays 2D/3D/4D arrays as Image, Labels, Points, Shapes, and Tracks layers; supports real-time annotation, plugin-based analysis, and headless screenshot export. Core visualization tool for bioimage analysis workflows. Use ImageJ/FIJI for macro-based processing; use napari for Python-native interactive visualization and plugin-based deep learning segmentation review."
pyhealth
by jaechang-hits
"PyHealth is a Python library for healthcare machine learning. Build clinical prediction models from EHR (Electronic Health Record) data: process MIMIC-III/IV, eICU, and OMOP-CDM datasets, encode medical codes (ICD, ATC, NDC), construct patient-level datasets, and train models (Transformer, RETAIN, GRASP, MedBERT) for tasks including mortality prediction, drug recommendation, readmission, and diagnosis prediction. Alternatives: FIDDLE (EHR preprocessing only), clinical-longformer (NLP on clinical notes only), ehr-ml (EHR embedding only)."
opencode-config
by serejaris
Use when configuring OpenCode CLI - changing default model, adding providers, setting baseURL, or troubleshooting model selection issues
subagent-creator
by tech-leads-club
Guide for creating AI subagents with isolated context for complex multi-step workflows. Use when users want to create a subagent, specialized agent, verifier, debugger, or orchestrator that requires isolated context and deep specialization. Works with any agent that supports subagent delegation. Triggers on "create subagent", "new agent", "specialized assistant", "create verifier".