ML Ops
Machine learning operations
ai-model-wechat
by TencentCloudBase
Use this skill when developing WeChat Mini Programs (小程序, 企业微信小程序, wx.cloud-based apps) that need AI capabilities. Features text generation (generateText) and streaming (streamText) with callback support (onText, onEvent, onFinish) via wx.cloud.extend.AI. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended) and DeepSeek (deepseek-v3.2 recommended). API differs from JS/Node SDK - streamText requires data wrapper, generateText returns raw response. NOT for browser/Web apps (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (not supported).
event-modeling
by lexler
Designs systems using Event Modeling.
ai-model-nodejs
by TencentCloudBase
Use this skill when developing Node.js backend services or CloudBase cloud functions (Express/Koa/NestJS, serverless, backend APIs) that need AI capabilities. Features text generation (generateText), streaming (streamText), AND image generation (generateImage) via @cloudbase/node-sdk ≥3.16.0. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended), DeepSeek (deepseek-v3.2 recommended), and hunyuan-image for images. This is the ONLY SDK that supports image generation. NOT for browser/Web apps (use ai-model-web) or WeChat Mini Program (use ai-model-wechat).
who-are-you
by Soul-Brews-Studio
Know ourselves - show identity, model info, session stats, and Oracle philosophy. Use when user asks "who are you", "who", "who we are", or wants to check current AI identity.
watch
by Soul-Brews-Studio
Learn from YouTube videos via Gemini transcription. Use when user says "watch", "transcribe youtube", "learn from video", or shares a YouTube URL to study.
fal-platform
by fal-ai-community
fal.ai Platform APIs for model management, pricing, usage tracking, and cost estimation. Use when user asks "show pricing", "check usage", "estimate cost", "setup fal", "add API key", or platform management tasks.
python-optimization
by jkitchin
Expert guidance for mathematical optimization in Python - systematic problem classification, library selection (scipy, pyomo, cvxpy, GEKKO), solver configuration, and implementation patterns for LP, QP, NLP, MIP, convex, and global optimization problems
model-evaluation
by cosmix
Evaluates machine learning models for performance, fairness, and reliability using appropriate metrics and validation techniques. Covers training debugging, hyperparameter tuning, and production monitoring. Trigger keywords: model evaluation, metrics, accuracy, precision, recall, F1, F1-score, ROC, AUC, ROC-AUC, confusion matrix, cross-validation, k-fold, stratified, overfitting, underfitting, bias, variance, bias-variance tradeoff, hyperparameter, hyperparameter tuning, loss, loss function, metric, benchmark, benchmarking, model performance, classification metrics, regression metrics, RMSE, MSE, MAE, MAPE, R2, R-squared, train-test split, validation set, test set, hold-out, learning curve, validation curve, model selection, error analysis, residual analysis, ML testing, training issues, convergence, gradient, vanishing gradient, exploding gradient, training instability, LLM evaluation, language model evaluation, prompt engineering evaluation, A/B testing, champion-challenger, model monitoring, model drift, data drift, concept drift, model decay.
debugging
by cosmix
Systematically diagnoses and resolves software bugs, test failures, data quality issues, and performance problems using various debugging techniques and tools. Trigger keywords: debug, bug, error, exception, crash, issue, troubleshoot, fix, stack trace, diagnosis, diagnose, investigate, root cause, why, failing, broken, not working, unexpected, flaky, intermittent, regression, performance degradation.
paper-assembly
by lingzhi227
Orchestrate the full paper pipeline end-to-end. Manage state propagation between phases (literature → plan → code → experiments → figures → tables → writing → review), support checkpointing and resumption. Use for assembling a complete paper from components.
3d-cv-labeling-2026
by 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).
fiftyone-embeddings-visualization
by voxel51
Visualizes datasets in 2D using embeddings with UMAP or t-SNE dimensionality reduction. Use when exploring dataset structure, finding clusters, identifying outliers, or understanding data distribution.
angular-forms
by 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.
surf
by nicobailon
Control Chrome browser via CLI for testing, automation, and debugging. Use when the user needs browser automation, screenshots, form filling, page inspection, network/CPU emulation, DevTools streaming, or AI queries via ChatGPT/Gemini/Perplexity/Grok/AI Studio.
economic-order-quantity
by kishorkukreja
When the user wants to calculate optimal order quantities, minimize total inventory costs using EOQ models, or determine the economic lot size. Also use when the user mentions "EOQ," "Wilson formula," "economic lot size," "order quantity optimization," "production batch size," "quantity discounts," "EPQ" (Economic Production Quantity), "backorder models," or "reorder point calculations." For multi-echelon systems, see multi-echelon-inventory. For stochastic models, see stochastic-inventory-models.
constraint-programming
by kishorkukreja
When the user wants to solve complex scheduling, allocation, or combinatorial problems using constraint programming (CP). Also use when the user mentions "constraint programming," "CP-SAT," "constraint satisfaction," "all-different constraint," "global constraints," "propagation," "search strategies," or when the problem has complex logical constraints, scheduling with disjunctive resources, or allocation problems. For MIP, see optimization-modeling. For metaheuristics, see metaheuristic-optimization.
letta-development-guide
by letta-ai
Comprehensive guide for developing Letta agents, including architecture selection, memory design, model selection, and tool configuration. Use when building or troubleshooting Letta agents.
golang-concurrency-patterns
by bobmatnyc
"Go concurrency patterns for production services: context cancellation, errgroup, worker pools, bounded parallelism, fan-in/fan-out, and common race/deadlock pitfalls"
pipeline
by TestAny-io
Testany 流水线 CRUD - 创建/查询/更新/删除 pipeline，编排用例执行顺序和变量传递（执行请用 /tests）
adf-validation-rules
by JosiahSiegel
Comprehensive Azure Data Factory validation rules, activity nesting limitations, linked service requirements, and edge-case handling guidance
azure-openai-2025
by JosiahSiegel
Azure OpenAI Service 2025 models including GPT-5, GPT-4.1, reasoning models, and Azure AI Foundry integration
mcp-tokenflux-images
by vaayne
Generate images using AI models via TokenFlux API. Use when creating AI-generated images, artwork, or visual content. Triggers on "generate image", "create picture", "AI art", "image generation", "TokenFlux".
pytm
by AgentSecOps
Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and automated security threat identification. Use when: (1) Creating threat models programmatically using Python code, (2) Generating data flow diagrams (DFDs) with automatic STRIDE threat identification, (3) Integrating threat modeling into CI/CD pipelines and shift-left security practices, (4) Analyzing system architecture for security threats across trust boundaries, (5) Producing threat reports with STRIDE categories and mitigation recommendations, (6) Maintaining threat models as code for version control and automation.
business-competitor-analysis
by manojbajaj95
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.