Plugins

2 plugins

Azure Content Safety SDK

For developers integrating Azure AI Content Safety across Python and TypeScript projects.

2 skills · plugin

AI-first Git CLI automation — atomic AI commits, co-change relations, autonomous git health agent, pre-tool hook safety, and workspace initialization

2 skills · plugin

Results for “ai-safety”

13 skills

azure-ai-contentsafety-py

Detect harmful user-generated and AI-generated content in text and images using Azure AI Content Safety SDK for Python.

azure-aigateway

Configure Azure API Management as an AI Gateway to govern AI models, MCP tools, and agents with policies for caching, rate limiting, content safety, and cost control.

azure-ai-contentsafety-ts

Analyze text and images for harmful content using Azure AI Content Safety, with customizable blocklists and severity thresholds.

Enforces safety gates, evidence-based debugging, anti-slack detection, and verification hooks when AI modifies files, configs, or deployments.

More results

azure-ai-contentsafety-java

Analyze text and images for harmful content using Azure AI Content Safety SDK for Java. Supports hate, violence, sexual content, and self-harm detection with blocklist management.

securing-api-gateway-with-aws-waf

Protect API Gateway endpoints with AWS WAF by configuring managed rule groups, rate limiting, bot control, IP reputation filtering, and monitoring.

24.6k · bundle

implementing-llm-guardrails-for-security

Builds input and output validation guardrails for LLM-powered applications to prevent prompt injection, data leakage, toxic content generation, and hallucinated outputs using NeMo Guardrails, Presidio, and Guardrails AI.

24.6k · bundle

Configure Gemini and Codex CLI tools with Cloudflare AI Gateway endpoints and MCP servers.

ai-trust-builders

Use when designing AI product trust, privacy, or honesty UX — cloud disclosure, voice/mic consent, transcript retention, memory ownership, AI labeling, caveats, or audit footprints. Trigger on disclose cloud, recording consent, watermark, incognito, or data-ownership settings.

Containerized security auditing and ethical hacking tools. All operations run in isolated Docker containers for safety.

ai-engineering-standards

Enforces production-grade Python and AI engineering standards for FastAPI, LangChain/LangGraph, RAG pipelines, and LLM integrations, covering type safety, error handling, testing, and security.

Orchestrates Gemini 3 Flash to audit Linux Kernel patches for memory safety, detect cost drifts in Terraform plans, and generate hardened Kubernetes security contexts.

cloudthinker-ai

Manages Ray clusters, jobs, Serve deployments, and distributed workloads via the Dashboard API and CLI, with discovery-first checks and safety guardrails.