MLOps
模型部署、评估与运维
LLM Council
dair-ai
Orchestrate multiple open-weight LLMs via Fireworks AI to deliberate on queries. Models respond individually, rank each other's responses, then a Chairman synthesizes the final answer. Use this skill when the user wants multiple AI perspectives, consensus-building, or the "LLM Council" approach inspired by Karpathy. Powered by fast, affordable open-weight models on Fireworks.
cobrapy
jimmc414
"Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis."
piper-tts-training
sammcj
Train custom TTS voices for Piper (ONNX format) using fine-tuning or from-scratch approaches. Use when creating new synthetic voices, fine-tuning existing Piper checkpoints, preparing audio datasets for TTS training, or deploying voice models to devices like Raspberry Pi or Home Assistant. Covers dataset preparation, Whisper-based validation, training configuration, and ONNX export.
invokeai-image-gen
sammcj
Generate images using InvokeAI's local API. Use when asked to generate, create, or make images with InvokeAI, FLUX.2 Klein, Z-Image Turbo, FLUX, or SDXL models. Supports text-to-image generation, automatic model detection, image download, and parameter selection based on model architecture.
israeli-pension-advisor
skills-il
Navigate the Israeli pension and savings system including pension funds (keren pensia), manager's insurance (bituach menahalim), training funds (keren hishtalmut), and retirement planning. Use when user asks about Israeli pension, "pensia", "keren hishtalmut", retirement savings, "bituach menahalim", pension contributions, or tax benefits from savings. Covers mandatory pension, voluntary savings, and withdrawal rules. Do NOT provide specific investment recommendations or fund performance comparisons.
3d-cv-labeling-2026
curiositech
Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).
angular-forms
analogjs
Build signal-based forms in Angular v21+ using the new Signal Forms API. Use for form creation with automatic two-way binding, schema-based validation, field state management, and dynamic forms. Triggers on form implementation, adding validation, creating multi-step forms, or building forms with conditional fields. Signal Forms are experimental but recommended for new Angular projects.
video-prompting
Square-Zero-Labs
Draft and refine prompts for video generation models (text-to-video and image-to-video). Use when a user asks for a "video prompt" or a model-specific prompt such as Ovi, Sora, Veo 3, Wan 2.2, or LTX-2, including requests like "text-to-video prompt", "image-to-video prompt", or "write a prompt for [model]".
pydantic-ai-testing
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.
pydantic-ai-common-pitfalls
existential-birds
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
jupyter
OpenHands
Read, modify, execute, and convert Jupyter notebooks programmatically. Use when working with .ipynb files for data science workflows, including editing cells, clearing outputs, or converting to other formats.
gitlab-webhooks
hookdeck
Receive and verify GitLab webhooks. Use when setting up GitLab webhook handlers, debugging token verification, or handling repository events like push, merge_request, issue, pipeline, or release.
mcp-code-execution
laurigates
Design and scaffold the code execution pattern for MCP-based agent systems. Use when building agents that interact with many MCP tools, when intermediate data is too large for model context, when you need loops/conditionals across tool calls, or when PII must stay out of the model context. Based on Anthropic's engineering guidance.
data-ml
baz-scm
Competence in data analytics and machine learning, enabling developers to build data-driven features and integrate AI/ML capabilities.
aws-sdk-java-v2-bedrock
giuseppe-trisciuoglio
Provides Amazon Bedrock patterns using AWS SDK for Java 2.x. Use when working with foundation models (listing, invoking), text generation, image generation, embeddings, streaming responses, or integrating generative AI with Spring Boot applications.
langchain4j-spring-boot-integration
giuseppe-trisciuoglio
Provides integration patterns for LangChain4j with Spring Boot. Handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications.
aeon
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.
threat-model-generation
Factory-AI
Generate a STRIDE-based security threat model for a repository. Use when setting up security monitoring, after architecture changes, or for security audits.
rails-presenter
ThibautBaissac
Creates presenter objects for view formatting using SimpleDelegator pattern with TDD. Use when extracting view logic from models, formatting data for display, creating badges/labels, or when user mentions presenters, view models, formatting, or display helpers.
role-creator
am-will
Create and install Codex custom agent roles in ~/.codex/config.toml, generate role config files, enforce supported keys, and guide users through required role inputs (model, reasoning effort, developer_instructions).
codex-subagent
am-will
Spawn Codex subagents via background shell to offload context-heavy work. Use for: deep research (3+ searches), codebase exploration (8+ files), multi-step workflows, exploratory tasks, long-running operations, documentation generation, or any other task where the intermediate steps will use large numbers of tokens.
opik-optimizer
vincentkoc
Optimize LLM prompts, tools, and agents in Opik using standardized optimizer workflows (prompt optimization, tool optimization, and parameter tuning), dataset/metric wiring, and result interpretation.
ai-ml-data-science
vasilyu1983
"End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining)."
ai-ml-timeseries
vasilyu1983
"Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptive forecasting."