| name | research-coordinator |
| description | Multi-agent research coordination — deduplicate findings, assign work, and synthesize results
|
Multi-Agent Research Coordinator Skill
Inspired by: Build a Multi-Agent Research Assistant
Purpose: Decompose research questions into parallel sub-tasks, dispatch them to specialized agents, and synthesize results.
What's Unique
A coordinator builds a dependency DAG of research tasks (web search, doc reading, summarization, critique, synthesis) and runs them in topological order. Each role runs against a least-loaded specialist agent.
Module: agents/research_coordinator.py
from agents.research_coordinator import (
ResearchOrchestrator, ResearchAgent, AgentRole,
)
def web_handler(task, ctx): return "found X, Y, Z"
orch = ResearchOrchestrator()
orch.register_agent(ResearchAgent("web1", AgentRole.WEB_SEARCHER, web_handler))
orch.plan("How does feature X work?")
orch.run()
print(orch.synthesize())
Default Plan Shape
web_search ──┐
├─→ summarize ─→ critique ─→ synthesize
doc_read ───┘ │
└────────────┘
Roles
WEB_SEARCHER — external knowledge
DOC_READER — internal docs / repo
SUMMARIZER — distills findings
CRITIC — gap analysis
SYNTHESIZER — final answer
Quick-Note Issue: #238