Results for “agent-management”

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

Expert en ComfyUI workflows avancé (install, custom nodes, model management, workflow design)

Expert en service mesh (Istio, Linkerd, mTLS, traffic management, observabilité, contexte DZ)

Merge the winning agent's branch into the base branch, archive losing branches via git tags, and clean up worktrees after an AgentHub competition session.

Design n8n AI agents with best practices for node selection, sub-node wiring, tool design, structured output, and memory management.

DAO Architect IA — Expert en architecture DAO (governance, proposals, voting mechanisms, treasury management)

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

Creates and manages AI agent teams for complex engineering tasks, with model routing, cost optimization, and performance evaluation.

Builds persistent multi-agent workflows on Claude Code using a kernel config, specialist agents, slash commands, file-based memory, and scheduled automation without external databases.

Build production-grade stateful AI agents using LangGraph, covering graph construction, state management, persistence, and human-in-the-loop patterns.

Deploy, manage, and govern MCP-based declarative agents in Microsoft 365 admin center with governance, assignments, and organizational distribution.

AI agent integration layer for the Pump SDK — agent instruction files, .well-known discovery, LLM context documents, 15+ skill files, MCP server prompts, and terminal management rules for GitHub Copilot and Gemini.

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.

Create and troubleshoot Ocana agents. Use when creating a new Ocana agent, refreshing/repairing management token auth, diagnosing `ocana_agent_create` failures, checking `gatewayReachable`, handling agents stuck in `provisioning`, debugging `226/NAMESPACE` or missing `/usr/bin/openclaw`, or testing lifecycle/reprovision flows for a newly created agent.

Provides foundational infrastructure for the agent ecosystem, including entity memory management, model routing, and integration with the 1ai-skills hook system.

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

Use when link building strategies, authority management, backlink acquisition, or link profile optimization is needed. This agent specializes in link building and authority management within the ContentForge AI ecosystem.

Trade perpetuals on Arbitrum's Nexus DEX with autonomous agent support, including position management, thesis publishing, and leaderboard tracking.

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

Tracks multi-step work across sessions using the hzl CLI, coordinating sub-agents with projects, tasks, checkpoints, and leases.

Claims-based authorization for agents and operations. Grant, revoke, and verify permissions for secure multi-agent coordination. Use when: permission management, access control, secure operations, authorization checks. Skip when: open access, no security requirements, single-agent local work.

Create and manage a Twitter/X agent with a persistent personality, automated posting workflows, and safety guardrails.

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, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK.

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

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, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check deployment status, verify serving endpoints, or clean up resources by undeploying models and deleting endpoints.

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

25 advanced engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Agent design, RAG, MCP servers, CI/CD, database design, observability, security auditing, release management, platform ops.

25 advanced engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Agent design, RAG, MCP servers, CI/CD, database design, observability, security auditing, release management, platform ops.

Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use windags-architect), specific tool implementation.

Uses the filesystem as a durable overflow layer for agent context, enabling scratch pads, plan persistence, sub-agent communication, dynamic skill loading, and log management.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when "langgraph, langchain agent, stateful agent, agent graph, react agent, agent workflow, multi-step agent, langgraph, langchain, agents, state-machine, workflow, graph, ai-agents, orchestration" mentioned.

Bridge any skill folder or directory of skill folders to Claude Code, Codex, generic Agents, and Grok using symlinks plus Grok bridge files.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.