multi agent market research desk

    by nowrich

    1

    A multi-agent research orchestrator that synthesizes technical, fundamental, and macro data into weighted briefs.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    See it in action

    You say

    Run a full desk analysis on NVIDIA (NVDA) ahead of their earnings call next week. Include macro context and technical levels.

    Your agent does

    Research Brief: NVIDIA (NVDA)

    Executive Summary

    • Bottom line: Bullish bias tempered by high macro risk.
    • Actionable recommendation: Maintain position; tight stops at $118.
    • Confidence level: High

    Evidence-Weighted Conclusions

    • AI demand remains primary growth driver — Evidence grade: A
    • Technical overextension on daily RSI — Evidence grade: B

    Points of Conflict

    • Macro vs. Fundamentals: Macro desk flags chip export curbs; Fundamentals desk sees offsetting data center demand.
    • Resolution: Fundamentals weighted higher due to verified backlog data.

    What you get

    Reconcile technical signals with fundamental asset valuations.Audit news sentiment against primary regulatory filings.Calculate evidence-weighted confidence scores for investment theses.Identify and resolve contradictory data points across different asset classes.

    About this skill

    The problem

    Single-source market analysis often ignores tail risks or macro shifts, leading to confirmation bias. Most analysts struggle to reconcile conflicting signals between technical indicators and fundamental valuations.

    What it does

    • Coordinates six specialist agent roles: Technicals, Fundamentals, Macro, News, Risk, and Verification.
    • Calculates evidence scores (0.0 to 1.0) based on source primary/secondary status and agent confidence levels.
    • Applies a formal conflict resolution framework to weigh shorter-term technicals against long-term fundamentals.
    • Generates a structured research brief with graded conclusions (A-D) and identified information gaps.
    • Filters out unverified claims or anonymous speculation using a dedicated Verification Agent.

    Why this beats prompting it yourself

    Instead of getting a generic summary, you get a rigorous multi-perspective audit. This skill enforces strict evidence-weighting rules and mathematical confidence scoring that a single-prompt approach lacks. It systematically surfaces contradictions between data sources rather than smoothing them over.

    Use cases

    • Conducting pre-trade due diligence on equities or crypto assets.
    • Synthesizing macro regimes with specific asset price action for portfolio rebalancing.
    • Vetting breaking news events against historical fundamentals and technical support levels.
    • Identifying tail risks and correlation threats before entering high-conviction positions.

    Known limitations

    Requires access to external data sources or search tools to populate agent reports effectively. Performance depends on the quality of underlying financial data provided in the context.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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