Analyst Society

Skill: Analyst Society Coordination

Overview

The 'Analyst Society' is a multi-agent coordination pattern designed to handle complex, multi-disciplinary analytical tasks. It uses a Supervisor to coordinate between specialized Workers.

Architectural Pattern

• Supervisor: The central router and decision-maker. It maintains the global state and delegates tasks to workers based on their expertise.
• SQL Worker: Specialized in data retrieval and schema discovery.
• Statistical Worker: Specialized in data exploration, visualization, and ML modeling (using dashboard workflows).

Coordination Logic (LangGraph)

1. Receive User Query: The Supervisor analyzes the intent.
2. Delegate:
   • If data is needed: Call SQL Worker.
   • If analysis/visualization is needed: Call Statistical Worker.
3. Verify: The Supervisor reviews worker output for completeness and fidelity.
4. Finalize: The Supervisor compiles the final response or report.

Standard State Schema

from typing import TypedDict, Annotated, List, Union
from pydantic import BaseModel, Field

class AnalystState(TypedDict):
    query: str
    data_context: str
    analytical_findings: List[str]
    current_worker: str
    iteration_count: int
    final_output: str

Discovery

Use mcp_plane_list_work_items to identify analytical tasks and mcp-fetch to source external data for the Analyst Society.