Results for “ai-agents”

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.

Authenticate AI agents with services using ERC-8004 onchain identity via Sign-In With Agent (SIWA).

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

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.

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

Generate AI images, videos, and music/audio from agents using the RunAPI CLI.

Coordinates multiple AI agents through a shared room: shared memory, task claiming, conflict detection, and destination tracking.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Scans AI agents, MCP servers, and skills for security vulnerabilities from the command line, detecting prompt injections, tool poisoning, toxic flows, malware payloads, and credential handling issues across 15+ risk categories.

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

A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.

Configure Warp terminal to share Claude Code's MCP servers and AI rules via File-based MCP + AGENTS.md. One-time UI toggles plus file sync. Use when onboarding Warp or after a Warp update resets settings.

Build type-safe AI agents and graph-based workflows with PydanticAI and PydanticGraph. Agent creation, function tools, capabilities, dependency injection, structured output, streaming, multi-agent patterns, testing, evals, and graph state machines. Use whenever you are building agents, tool-using LLM workflows, or graph-based state machines in Python.

Writes unit, smoke, and e2e tests for AI agents, covering tools, instructions, routing, citations, and guardrails.

MoonPay PayBox payment vault for AI agents — official MCP at https://api.paybox.sh/mcp, OAuth 2.1, scoped credentials, and Cheshire mcp-server proxy tools (get_paybox_*).

Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.

Expert in Cursor AI IDE - the leading AI-powered code editor. Covers Rules files for project-specific AI behavior, Plan Mode for structured development, Background Agents for parallel work, and advanced features like voice mode and browser integration. Essential for developers maximizing AI-assisted coding productivity. Use when "cursor ai, cursor rules, .cursorrules, cursor composer, cursor agent, plan mode, background agent, cursor tips, cursor, ide, ai-coding, editor, productivity, agent, developer-tools" mentioned.

Enhances plain-language requests into structured, reviewable prompts and inspects a self-hosted MCP gateway with provider-free defaults.

Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents). Use when the user wants to register their agent identity on-chain, create an agent profile, claim an agent NFT, set up agent reputation, or make their agent discoverable. Handles bridging ETH to mainnet, IPFS upload, and on-chain registration.

Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.

Analyzes Android apps to identify key user workflows for AppFunctions such as creating a note, playing media, or sending an automated or AI agent triggered message, voice commands, or system shortcuts, without needing to open the app UI. Generates Kotlin code to expose these workflows to the Android system, allowing agents to discover and execute them on-device. Also refines KDoc documentation to ensure AI agents correctly understand and use the provided functionality.

AAWP (AI Agent Wallet Protocol) — the only crypto wallet protocol built exclusively for AI Agents on EVM-compatible blockchains and Solana. Not for humans. The signer is the AI Agent itself, cryptographically bound at wallet creation. Supports wallet lifecycle management, token transfers, DEX swaps, cross-chain bridging, Solana native trading (Pump.fun SDK + Jupiter), token launches, DCA automation, and price alerts.

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

Provides persistent, compounding memory for AI agents across sessions using local markdown files, with optional Supabase-backed semantic search.

Build durable backend AI agents with the eve framework. Use when creating, editing, or debugging an eve project — agent instructions, skills, tools, connections, channels, sandboxes, subagents, schedules, or evals.

Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.

Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.

Provides 25 paid HTTP endpoints on Base mainnet that bill agents per call in USDC for web search, AI analysis, crypto and stock data, SEC filings, company intelligence, news, sentiment scoring, and a macro dashboard, returning structured JSON.

Control tmux panes and communicate between AI agents. Use this skill whenever the user mentions tmux panes, cross-pane communication, sending messages to other agents, reading other panes, managing tmux sessions, or interacting with processes running in tmux. Includes tmux-bridge CLI for agent-to-agent messaging and raw tmux commands for direct session control.

Build teams of autonomous AI agents that collaborate to solve complex tasks using role-based delegation, memory, and sequential or hierarchical execution.

Install and configure Acontext, a memory layer for AI agents that provides persistent sessions, file storage, and skill management.