Ross ROSS = Recommend OSS · open-source software intelligence for agents

SkyworkAI/DeepResearchAgent

DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains. observed · 2026-08-28

github.com/SkyworkAI/DeepResearchAgent · homepage · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

68/100

  • Activity 80
  • Release rhythm 72
  • Longevity 33
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 0
  • age_days: 470
  • days_rel: 190
  • days_push: 121
  • n_releases_24m: 2

Full methodology

Adoption not part of the score

3532 stars · 453 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DeepResearchAgent is a Python framework for hierarchical multi-agent systems that combines a top-level planning agent with specialized lower-level agents for deep research and general-purpose task solving. It provides a self-evolution protocol and runtime with protocol-registered resources (prompts, agents, tools, environments, memory) and a closed-loop optimization layer for iterative agent improvement.

Use cases

  • build a hierarchical multi-agent system for deep research
  • automate task decomposition across specialized agents
  • run a deep research agent on the GAIA benchmark
  • self-improve LLM agent prompts and solutions iteratively
  • orchestrate tool-calling agents with memory and tracing
  • evaluate agents in browser, filesystem, or trading environments

When to choose

  • you need coordinated multi-agent planning and task decomposition
  • you want an evolvable agent runtime with versioning, tracing, and rollback
  • you need composable agents, tools, environments, and memory in one Python framework
  • you are benchmarking general-purpose agents on tasks like GAIA

When to avoid

  • you need a simple single-agent chatbot with minimal setup
  • you want a production-ready managed agent service rather than a framework
  • your use case is unrelated to LLM-based agents or research automation

Facets

framework · maturity active

agent-framework llm-inference prompt-engineering rag workflow-automation web-scraping artificial-intelligence large-language-models developer-tools python cli cross-platform multi-agent hierarchical-agents self-evolution deep-research gaia-benchmark tool-calling agent-memory llm-optimization ai-agents automation

1 source

Member repositories

RepositoryRoleHealth v2
SkyworkAI/DeepResearchAgentmain68

For agents

markdown · JSON · MCP: product_card(name="SkyworkAI/DeepResearchAgent")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem