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aws-sagemaker
Amazon SageMaker for building, training, and deploying machine learning models. Use for SageMaker AI endpoints, model training, inference, MLOps, and AWS machine learning services.
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tools machine learning AI 技能
发现 tools machine learning 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
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GitHub
nvidia-api
NVIDIA API documentation for integrating NVIDIA services. Use for NVIDIA NIM (NVIDIA Inference Microservices), LLM APIs, visual models, multimodal APIs, retrieval APIs, healthcare APIs, and CUDA-X microservices...
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GitHub
monitoring-observability
Production monitoring and observability for LLM applications with AgentOps session tracking, Google Cloud Observability integration, and Dynatrace monitoring. Provides real-time performance metrics, error track...
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GitHub
google-aistudio-anti-pattern-detection
Detects and corrects common anti-patterns generated by Google AI Studio and similar tools.
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GitHub
expertise-system-implementation
Guides expertise system implementation: multi-path recognition, hierarchy (local → city → state → national), golden experts, visit quality. Use when implementing expertise calculations, expert recognition, or e...
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GitHub
behavioral-modes
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
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GitHub
behavioral-modes
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
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GitHub
ai2ai-privacy-validation
Enforces AI2AI privacy validation: anonymized data exchange, no personal identifiers, privacy-preserving learning. Use when implementing AI2AI features, validating privacy, or ensuring privacy compliance.
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GitHub
ai-integration
Expert intégration IA/ML dans applications web - LLMs, RAG, vector databases, embeddings. Utilise ce skill quand: (1) intégration API OpenAI/Claude/Mistral, (2) mise en place RAG, (3) vector databases, (4) prom...
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GitHub
kpi-calculation
Calculate and track key performance indicators (KPIs) from pilot data and defined metrics. Use when deriving success metrics, benchmarking performance against objectives, or preparing quantitative reports and d...
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GitHub
bias-and-fairness-auditing
Audit pilot data, models, and workflows for bias and inclusivity issues. Use when evaluating fairness across demographic groups, identifying algorithmic biases, and recommending mitigation strategies to ensure...
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GitHub
tune-accuracy
Run accuracy evaluation/tuning for RQ-SCAN and generate reports.
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GitHub
mcp-tool-definition
best practices for defining MCP tools using JSON schemas. Use this to design robust `inputSchema`, `outputSchema`, and `annotations` that guide the model effectively.
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GitHub
tabular-ml-modeling
State-of-the-art machine learning for large-scale tabular data (millions of rows, thousands of features). Use when building predictive models on tabular/structured data including regression and classification t...
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GitHub
prompt-engineering
Prompt Engineering avanzado 2025 - Context Engineering, DSPy, optimización de tokens y seguridad.
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GitHub
context-engineering
Advanced 2026 context curation patterns (Nvidia Eureka, Context Hygiene, RLMF) for autonomous agents.
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GitHub
data-analysis
Data analysis workflows and patterns for processing, analyzing, and visualizing data using Python data science libraries.
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GitHub
ai-data-analyst
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create...
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GitHub
learn
Unified learning skill - log decisions (--decision), review launches (--launch), or extract patterns from history (--patterns)
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GitHub
analyze
Unified analysis skill - Python data analysis (--data) or KB gap identification (--kb)
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GitHub
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt temp...
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GitHub
c4-diagrams
C4 model architecture diagrams
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GitHub
spaced-repetition
Work with the spaced repetition learning algorithm and review system
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GitHub
logprob-prefill-analysis
Reproduces the full prefill sensitivity analysis pipeline for reward hacking indicators. Use when evaluating how susceptible model checkpoints are to exploit-eliciting prefills, computing token-based trajectori...
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。