Results for “agent-progress”

Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.

Orchestrates multi-agent project builds with persistent state, parallel execution, and atomic git commits.

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.

Build AI agents on Cloudflare Workers using the Agents SDK, covering stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, and browser automation.

Scaffold and develop AI agents using OpenAI Agents SDK patterns, covering agent definition, tools, guardrails, handoffs, context, RAG pipelines, streaming, API routes, testing, and debugging.

Discovers, installs, and manages AI agent skills from agentskill.sh, including searching, installing mid-session, scanning for security issues, and providing feedback.

Build, deploy, and manage continuous AI agents using a visual workflow editor or development toolkit.

Add a batteries-included agent component to React/Next.js apps with runtime, streaming, human-in-the-loop approvals, and client-side tools.

Designs or reviews Agentforce agent actions, covering Flow, Apex invocable, and prompt-template actions, including naming, input/output contracts, confirmation, and error behavior.

Orchestrate multi-agent coding tasks via Claude DevFleet: plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.

Implements an ACP (Agent Communication Protocol) server that wraps a LangGraph-based deep agent, enabling session management, streaming message handling, and tool call progress tracking.