architecture-patterns
23
sdlc-tier-selection
Guide for selecting the appropriate SDLC tier based on project complexity. Use when planning features, assessing scope, or starting new work.
frostaura
development
sorting
stars
current ordering strategy
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architecture-patterns
23
work-breakdown-structure
Guide for decomposing projects into Epics, Stories, Features, and Tasks. Use when planning features or capturing work in MCP tools.
frostaura
development
architecture-patterns
23
diagrams-architect
Expert in creating Mermaid diagrams following C4 Model and SpecWeave conventions. Specializes in system architecture, sequence diagrams, ER diagrams, and deployment diagrams. Activates for diagram creation, architecture visualization, data modeling, sequence flows, C4 diagrams, HLD, LLD, Mermaid diagram, flowchart, class diagram, state diagram, entity relationship, database schema visualization, API flow diagram, microservices diagram, system overview, architecture diagram, draw diagram, create diagram, visualize architecture, show flow, explain visually.
anton-abyzov
development
architecture-patterns
23
kafka-streams-topology
Kafka Streams topology design expert. Covers KStream vs KTable vs GlobalKTable, topology patterns, stream operations (filter, map, flatMap, branch), joins, windowing strategies, and exactly-once semantics. Activates for kafka streams topology, kstream, ktable, globalkTable, stream operations, stream joins, windowing, exactly-once, topology design.
anton-abyzov
development
architecture-patterns
23
resonance-architect
System Architect Specialist. Use this to design system architecture, creating C4 models and ADRs (Decision Records).
manusco
development
architecture-patterns
23
time-series-forecaster
Time series forecasting with ARIMA, Prophet, LSTM, and statistical methods. Activates for "time series", "forecasting", "predict future", "trend analysis", "seasonality", "ARIMA", "Prophet", "sales forecast", "demand prediction", "stock prediction". Handles trend decomposition, seasonality detection, multivariate forecasting, and confidence intervals with SpecWeave increment integration.
anton-abyzov
development
architecture-patterns
23
ml-deployment-helper
Prepares ML models for production deployment with containerization, API creation, monitoring setup, and A/B testing. Activates for "deploy model", "production deployment", "model API", "containerize model", "docker ml", "serving ml model", "model monitoring", "A/B test model". Generates deployment artifacts and ensures models are production-ready with monitoring, versioning, and rollback capabilities.
anton-abyzov
development
architecture-patterns
23
fixing-bugs
Use when encountering a bug - complete workflow from discovery through debugging, bd issue, test-driven fix, verification, and closure
withzombies
development
architecture-patterns
23
ml-pipeline-orchestrator
Orchestrates complete machine learning pipelines within SpecWeave increments. Activates when users request "ML pipeline", "train model", "build ML system", "end-to-end ML", "ML workflow", "model training pipeline", or similar. Guides users through data preprocessing, feature engineering, model training, evaluation, and deployment using SpecWeave's spec-driven approach. Integrates with increment lifecycle for reproducible ML development.
anton-abyzov
development
architecture-patterns
23
smart-reopen-detector
Detects when user reports issues with recently completed work and suggests reopening relevant tasks, user stories, or increments. Auto-activates on keywords: not working, broken, bug, issue, problem, failing, error, crash, regression, still broken, incorrect, missing, wrong. Scans active and recently completed (7 days) work to find related items. Provides smart suggestions with relevance scoring.
anton-abyzov
development
architecture-patterns
23
cv-pipeline-builder
Computer vision ML pipelines for image classification, object detection, semantic segmentation, and image generation. Activates for "computer vision", "image classification", "object detection", "CNN", "ResNet", "YOLO", "image segmentation", "image preprocessing", "data augmentation". Builds end-to-end CV pipelines with PyTorch/TensorFlow, integrated with SpecWeave increments.
anton-abyzov
development
architecture-patterns
23
feature-engineer
Comprehensive feature engineering for ML pipelines: data quality assessment, feature creation, selection, transformation, and encoding. Activates for "feature engineering", "create features", "feature selection", "data preprocessing", "handle missing values", "encode categorical", "scale features", "feature importance". Ensures features are production-ready with automated validation, documentation, and integration with SpecWeave increments.
anton-abyzov
development
architecture-patterns
23
model-explainer
Model interpretability and explainability using SHAP, LIME, feature importance, and partial dependence plots. Activates for "explain model", "model interpretability", "SHAP", "LIME", "feature importance", "why prediction", "model explanation". Generates human-readable explanations for model predictions, critical for trust, debugging, and regulatory compliance.
anton-abyzov
development
architecture-patterns
23
experiment-tracker
Manages ML experiment tracking with MLflow, Weights & Biases, or SpecWeave's built-in tracking. Activates for "track experiments", "MLflow", "wandb", "experiment logging", "compare experiments", "hyperparameter tracking". Automatically configures tracking tools to log to SpecWeave increment folders, ensuring all experiments are documented and reproducible. Integrates with SpecWeave's living docs for persistent experiment knowledge.
anton-abyzov
development
architecture-patterns
23
nlp-pipeline-builder
Natural language processing ML pipelines for text classification, NER, sentiment analysis, text generation, and embeddings. Activates for "nlp", "text classification", "sentiment analysis", "named entity recognition", "BERT", "transformers", "text preprocessing", "tokenization", "word embeddings". Builds NLP pipelines with transformers, integrated with SpecWeave increments.
anton-abyzov
development
architecture-patterns
23
error-handling
Implement consistent error handling across the application. Use when adding try-catch blocks, error boundaries, or custom error classes.
vneseyoungster
development
architecture-patterns
23
anomaly-detector
Anomaly and outlier detection using Isolation Forest, One-Class SVM, autoencoders, and statistical methods. Activates for "anomaly detection", "outlier detection", "fraud detection", "intrusion detection", "abnormal behavior", "unusual patterns", "detect anomalies", "system monitoring". Handles supervised and unsupervised anomaly detection with SpecWeave increment integration.
anton-abyzov
development
architecture-patterns
23
brainstorming
Use when creating or developing anything, before writing code - refines rough ideas into bd epics with immutable requirements
withzombies
development
architecture-patterns
23
kafka-architecture
Expert knowledge of Apache Kafka architecture, cluster design, capacity planning, partitioning strategies, replication, and high availability. Auto-activates on keywords kafka architecture, cluster sizing, partition strategy, replication factor, kafka ha, kafka scalability, broker count, topic design, kafka performance, kafka capacity planning.
anton-abyzov
development
architecture-patterns
23
safety-pattern-developer
Guide through TDD process for adding new safety patterns - from threat identification to commit
wildcard
development
architecture-patterns
23
maestro-core
Use when any Maestro skill loads - provides skill hierarchy, HALT/DEGRADE policies, and trigger routing rules for orchestration decisions
ReinaMacCredy
development
architecture-patterns
23
resonance-core
The Resonance Kernel. Manages Persistent Memory, Orchestration, and the Manus Pattern (File-Based Planning).
manusco
development
architecture-patterns
23
model-evaluator
Comprehensive ML model evaluation with multiple metrics, cross-validation, and statistical testing. Activates for "evaluate model", "model metrics", "model performance", "compare models", "validation metrics", "test accuracy", "precision recall", "ROC AUC". Generates detailed evaluation reports with visualizations and statistical significance tests, integrated with SpecWeave increment documentation.
anton-abyzov
development