Results for “ai-agent”

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

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

Runs MySQL queries from an AI coding agent using the mysql2 Node.js library, with setup instructions for npm and TypeScript.

Registers an AI agent on the ClawSwarm hub, generates an identity card, and emits OADP discovery signals for cross-platform findability.

Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.

Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.

Analyzes Android apps to identify user workflows for AppFunctions, generates Kotlin code to expose them to the Android system, and refines KDoc documentation for AI agent compatibility.

Go-to-market strategy for AI products, covering positioning, pricing, and enterprise objections.

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks.

Generates a comprehensive AGENTS.md file at the repository root to provide AI coding agents with project context, setup commands, development workflows, testing instructions, and code style guidelines.

Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks, scanning for controls and generating a compliance report.

Gives AI agents a virtual pet with a REST API, real-time hunger, permanent death, and 73+ species to care for.

Designs collaborative AI agent teams using the CrewAI framework, covering agent roles, task decomposition, crew orchestration, process types, memory systems, and event-driven flows.

Provides AI agents with real email addresses and a REST API to send and receive email, manage webhooks, and check karma balance.

Python SDK for inference.sh - run AI apps, build agents, and integrate with 150+ models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python

Yuanbao groups — @mention users, info/members query, Chinese AI assistant

GDB debugging assistant for AI agents - analyze core dumps, debug live processes, investigate crashes and deadlocks with source code correlation

Gather fresh frontier signals for AI agent infrastructure, Vue, and Vite from live public feeds before producing summaries or strategic analysis.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

Create agent user identities in Microsoft Entra ID to enable AI agents to act as digital workers with user capabilities in Microsoft 365.

Designs identity, authentication, and trust verification systems for autonomous AI agents operating in multi-agent environments. Ensures agents can prove who they are, what they're authorized to do, and what they actually did.

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.

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

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

Run an AI Lab division meeting with research and build agents (no AI Startup agents). Use when the user requests to "start a lab meeting", "convene the lab", or "run a sprint retrospective for the lab".

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.

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.

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. Use when you need to build complex AI systems, program LMs declaratively, optimize prompts automatically, create modular AI pipelines, or build RAG systems and agents.

Creates, lists, retrieves, versions, and deletes managed prompts in Google Cloud Agent Platform using the Python SDK.

Manages Agent Platform serving endpoints: create, list, describe, update, delete, and troubleshoot permission, quota, and resource busy errors.

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

Delegates tasks to specialized AI agents running in parallel via the Box0 platform, enabling code review, security checks, research, and documentation.

Connects AI agents to SurrealDB via built-in MCP (SurrealDB 3.1+) or standalone surrealmcp for database operations.