Results for “ai-agents”

Adds observability and debugging for AI-assisted application workflows using Sentry.

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter.

Operates Redpanda's Agentic Data Plane: manages AI agents, MCP servers, LLM providers, budgets, guardrails, and Cedar access policies via the `rpk ai` CLI and API, including OAuth wiring and spend/transcript insights.

Provides an MCP server for managing infrastructure with Pulumi, enabling infrastructure-as-code operations through AI agents.

Build AI applications using the Azure AI Projects SDK for TypeScript, managing agents, connections, deployments, datasets, indexes, and evaluations.

Installs and configures Apache Airflow via pip or Docker, with guidance on constraints, requirements, and deployment options.

Sets up Google's agents-cli toolkit and guides through the full agent development lifecycle: scaffold, build, evaluate, deploy, publish, and monitor on Gemini Enterprise Agent Platform.

Guides users to install and run the ai-ready skill for making repositories AI-ready with AGENTS.md, instructions, and CI workflows.

Spawns multiple parallel AI agents that compete on the same task using isolated git worktrees, evaluates results, and merges the best solution.

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.

Design, operate, and troubleshoot OCI services including OKE, IoT, Functions, and Enterprise AI with OCI Generative AI models, agents, RAG, and cost estimation.

Registers prompt-based AI agents in Azure AI Foundry via REST API from a local JSON manifest, making them immediately available for invocation.

Run multiple AI agents against a product, SDK, or docs site to score setup friction, speed, efficiency, error recovery, and doc quality from a minimal prompt.

Designs and implements a Google Cloud solution for live, bidirectional multimodal streaming workloads with AI agents, covering requirements discovery, architecture design, and deployment planning.

Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task.

Sets up the Manifest observability plugin for AI agents, including installation, API key configuration, and verification.

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations, detecting attack vectors where attacker-controlled input reaches AI agents in CI/CD pipelines.

Navigate Oracle Cloud Infrastructure's Enterprise AI services: choose models, build agents with RAG and tools, estimate costs, secure access, and integrate with Oracle Database, APEX, and other platform services.

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK, with support for function tools, hosted tools, MCP servers, conversation threads, and streaming responses.

Configures dynamic threshold alerting policies for Google Cloud Vertex AI Agent Platform agents, monitoring latency, error rates, and quality metrics using Terraform and PromQL.

Compares coding agents head-to-head on reproducible tasks, measuring pass rate, cost, time, and consistency.

Installs and configures the Manifest observability plugin for AI agents, including API key setup, custom endpoint configuration, and troubleshooting.

Create and manage OAuth2-capable identities for AI agents using Microsoft Graph beta API.

Installs and configures the Manifest observability plugin for AI agents, including API key setup, endpoint configuration, and connection verification.

Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

Orchestrate parallel AI agent sessions using dmux, a tmux pane manager for agent harnesses like Claude Code and Codex.

Build WinDAGs — the orchestration platform where AI agents accumulate genuine expertise through DAGs of skillful agents. Covers DAG design, execution engines, meta-DAG architecture, skill selection, dynamic mutation, visualization, and deployment. Activate on "windags", "agent DAG", "DAG of agents", "workflow orchestration", "agent pipeline", "dynamic DAG", "meta-DAG", "build windags", "implement windags". NOT for understanding WHY decisions were made (use windags-avatar), creating individual skills (use skill-architect), or managing skill libraries (use windags-librarian).

Provides a structured guide for creating effective skills for AI coding agents, with emphasis on Azure SDKs and Microsoft Foundry services.