MLOps

Operacions d’aprenentatge automàtic

Skills: 697–720 de 2097
AzureCosmosDB

cosmosdb-best-practices

AzureCosmosDB

Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.

Processament de dades 59 fa 8 mesos
oyi77

model-router

oyi77

Intelligent model routing via subagents - automatically spawn the right model for each task complexity

Automatització 17 fa 8 mesos
runkids

audit-context-building

runkids

Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.

MLOps 16 fa 7 mesos
mfwarren

unit-economics

mfwarren

Production-ready entrepreneurship skills for Claude Code — marketing, sales, operations, finance, and leadership. 24 skills built by a founder, for founders.

Finances 81 fa 8 mesos
mastepanoski

owasp-ai-testing

mastepanoski

AI trustworthiness testing using OWASP AI Testing Guide v1. Execute 44 test cases across 4 layers (Application, Model, Infrastructure, Data) with practical payloads and remediation.

Processament de dades 58 fa 8 mesos
am-will

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).

Operacions amb fitxers 1 k fa 8 mesos
hmans

bubbletea

hmans

Browse Bubbletea TUI framework documentation and examples. Use when working with Bubbletea components, models, commands, or building terminal user interfaces in Go.

Generació de documentació 955 fa 10 mesos
personamanagmentlayer

data-science-expert

personamanagmentlayer

Expert-level data science, analytics, visualization, and statistical modeling

Analítica 44 fa 9 mesos
am-will

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.

Revisió de codi 1 k fa 9 mesos
akaszubski

realign-meta-framework

akaszubski

Production-ready Claude Code 2.0 setup for autonomous development

MLOps 34 fa 8 mesos
ThibautBaissac

authentication-flow

ThibautBaissac

Implements authentication using Rails 8 built-in generator. Use when setting up user authentication, login/logout, session management, password reset flows, or securing controllers.

Autenticació 669 fa 9 mesos
ThibautBaissac

rails-architecture

ThibautBaissac

Guides modern Rails 8 code architecture decisions and patterns. Use when deciding where to put code, choosing between patterns (service objects vs concerns vs query objects), designing feature architecture, refactoring for better organization, or when user mentions architecture, code organization, design patterns, or layered design.

Bases de dades 669 fa 9 mesos
personamanagmentlayer

ml-expert

personamanagmentlayer

Expert-level machine learning, deep learning, model training, and MLOps

Processament de dades 44 fa 9 mesos
hollandkevint

data-product-thinking

hollandkevint

First-principles reasoning for data product decisions. Frames problems as data products, not dashboards or pipelines. Use when evaluating data product strategy, making build-vs-buy decisions, scoping data product features, assessing product-market fit for data offerings, or when someone asks "should we build this data product?"

Processament de dades 5 fa 8 mesos
hollandkevint

ethical-risk-assessment

hollandkevint

Ethical data risk evaluation, bias testing protocols, and governance practices for data products. Use when evaluating ML/AI features for fairness, designing bias testing protocols, planning phased rollouts for high-risk changes, reviewing data governance practices, or when someone asks "could this model be biased?" or "how do we ship AI features responsibly?" For HIPAA-specific guidance, see healthcare-data-domain.

Processament de dades 5 fa 8 mesos
GhostScientist

hugging-face-space-deployer

GhostScientist

Create, configure, and deploy Hugging Face Spaces for showcasing ML models. Supports Gradio, Streamlit, and Docker SDKs with templates for common use cases like chat interfaces, image generation, and model comparisons.

Desenvolupament d’API 5 fa 10 mesos
NeverSight

megaeth-developer

NeverSight

End-to-end MegaETH development playbook (Feb 2026). Covers wallet operations, token swaps (Kyber Network), eth_sendRawTransactionSync (EIP-7966) for instant receipts, JSON-RPC batching, real-time mini-block subscriptions, storage-aware contract patterns (Solady RedBlackTreeLib), MegaEVM gas model, WebSocket keepalive, bridging from Ethereum, and debugging with mega-evme. Use when building on MegaETH, managing wallets, sending transactions, or deploying contracts.

Processament de dades 218 fa 8 mesos
xu-xiang

django-patterns

xu-xiang

Django 架构模式、使用 DRF 的 REST API 设计、ORM 最佳实践、缓存、信号(Signals)、中间件(Middleware)以及生产级 Django 应用。

Memòria cau 2 k fa 8 mesos
zxc123aa

cc-proxy-detector

zxc123aa

检测 Claude Code 中转站的真实后端来源(Anthropic 官方 / AWS Bedrock Kiro / Google Vertex AI Antigravity / 疑似伪装)。当用户想要检测中转站渠道来源、验证 API 是否为官方直连、识别中转站伪装、扫描多模型混合渠道时使用。触发词包括"检测渠道"、"检测中转"、"proxy detect"、"渠道来源"、"是不是官方"。

Desenvolupament d’API 47 fa 8 mesos
wundercorp

jupyter-notebook

wundercorp

"Iterative Python via live Jupyter kernel (hamelnb)."

Desenvolupament d’API 26 fa 1 mes
agenticnotetaking

pipeline

agenticnotetaking

End-to-end source processing -- seed, reduce, process all claims through reflect/reweave/verify, archive. The full pipeline in one command. Triggers on "/pipeline", "/pipeline [file]", "process this end to end", "full pipeline".

Automatització 3,5 k fa 8 mesos
openamer

DSPy: Declarative Language Model Programming

openamer

The self-improving, self-learning open-source AI agent. Background Computer-Use, A2A Swarm, Vector Memory, Plugin System, Voice, Smart Approvals - 100/100 Score. Windows-native.

Generació de codi 8 fa 3 mesos
openamer

Segment Anything Model (SAM)

openamer

The self-improving, self-learning open-source AI agent. Background Computer-Use, A2A Swarm, Vector Memory, Plugin System, Voice, Smart Approvals - 100/100 Score. Windows-native.

Generació de codi 8 fa 3 mesos
openamer

TensorRT-LLM

openamer

The self-improving, self-learning open-source AI agent. Background Computer-Use, A2A Swarm, Vector Memory, Plugin System, Voice, Smart Approvals - 100/100 Score. Windows-native.

MLOps 8 fa 3 mesos