Orchestrate multi-step tasks with planning, web search, and parallel subagents.
npx skills add https://github.com/lgwanai/openforce --skill deerflow-skill
Please help me install this Agent Skill. Skill: deerflow-skill Source: https://github.com/lgwanai/openforce/tree/main/skills/deerflow Command: npx skills add https://github.com/lgwanai/openforce --skill deerflow-skill
This Skill orchestrates complex, multi-step work so you can research, plan, and delegate tasks without setting up a server or managing agents manually.
Use the deerflow-skill Skill to analyze the src directory and propose an improvement plan in a single request with web research when needed.
High-intent search queries and answers about installing and using this skill.
To orchestrate multi-step agent tasks with web research, you can use an embedded runtime that combines structured planning, tool calling, and subagent delegation. This approach handles task decomposition and streams execution output directly without requiring a separate server.
Yes, LangGraph supports parallel subagent delegation for complex workloads. By utilizing an embedded agent runtime with a dedicated harness, you can decompose heavy tasks into parallel execution streams and manage them through structured tool orchestration.
The best way to plan code review investigations using current web sources is to employ an orchestration skill with fuzzy keyword-to-mode routing. It automatically retrieves up-to-date web information and structures the analysis into a multi-step execution plan.
Tool gating restricts agent capabilities using an allowed-tools list, while robust error handling intercepts recursion, timeouts, quota, and authentication failures during streaming execution. This mechanism provides user-facing guidance to gracefully recover from runtime issues.
No, you do not need a separate server to manage agent orchestration and task planning. You can embed the agent runtime directly within your local environment, utilizing a harness and libraries like LangChain to execute structured plans and tool calls.
Switch between flash, standard, pro, and ultra presets to match task complexity. Use flash for simple queries and ultra for large workloads requiring deep reasoning or parallel subagent delegation, ensuring efficient resource allocation across different orchestration tiers.
jackjin1997Configure agent harness middleware for LangChain/LangGraph applications.
The-RabakTransform feature descriptions into structured project plans with acceptance criteria.
open-gitagentSearch the web for current news and information via the Tavily API.
LincyawCreate and configure Deep Agents applications using LangChain and LangGraph.
