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Found 131 Skills
Scoring formulas and analytical frameworks for GitHub workflow agents. Covers repository health scoring (0-100, A-F grades), priority scoring for issues/PRs/discussions, confidence levels for analytics findings, delta tracking (Fixed/New/Persistent/Regressed), velocity metrics, contributor metrics, bottleneck detection, and trend classification. Use when computing scores, tracking remediation progress, building prioritized dashboards, or detecting workflow bottlenecks.
Multi-source AI news aggregation and digest generation with deduplication, classification, and source tracing. Supports 20+ sources, 5 theme categories, multi-language output (ZH/EN/JA), and image export.
AI governance and compliance guidance covering EU AI Act risk classification, NIST AI RMF, responsible AI principles, AI ethics review, and regulatory compliance for AI systems.
Identifies subdomains and suggests bounded contexts in any codebase following DDD Strategic Design. Use when analyzing domain boundaries, identifying business subdomains, assessing domain cohesion, mapping bounded contexts, or when the user asks about DDD strategic design, domain analysis, or subdomain classification.
The industry standard library for machine learning in Python. Provides simple and efficient tools for predictive data analysis, covering classification, regression, clustering, dimensionality reduction, model selection, and preprocessing.
Structured interactive questionnaire framework for gathering requirements from users. Uses A/B/C/D/E multiple choice patterns with additive vs exclusive question classification.
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows.
Alibaba Cloud APIG Migration Skill. Migrate Kubernetes nginx Ingress resources to Alibaba Cloud API Gateway (APIG, ingressClass: apig). Users provide Ingress YAML (paste, file, or directory) — no cluster access required for analysis. Covers annotation compatibility classification, Higress native mapping, built-in plugin selection, custom WasmPlugin development, migrated Ingress YAML generation, and migration report with deployment guide. Triggers: "nginx ingress migration", "APIG compatibility", "gateway migration", "ingress-nginx to APIG", "nginx迁移", "网关迁移", "Ingress兼容性分析", "APIG迁移", "迁移评估", "annotation兼容性", "WasmPlugin开发".
Design conversational AI chatbots including intent recognition, slot filling, dialogue flow, and response generation. Use this skill when the user needs to build a chatbot, design conversation flows, implement intent classification, or improve chatbot accuracy — even if they say 'build a chatbot', 'our bot doesn't understand users', 'design a FAQ bot', or 'improve our chatbot's responses'.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
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.