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GlynnCarson

tradingview-mcp

by GlynnCarson

multi_agent_analysis

Read-only

Debates technical, sentiment, and risk analyses to produce a final trading decision for any symbol across global exchanges.

Instructions

Run a multi-agent debate (Technical, Sentiment, Risk) for a specific symbol.

Args: symbol: Symbol — crypto: "BTCUSDT"; stocks: "COMI" (EGX), "THYAO" (BIST), "600519" (SSE), "300251" (SZSE), "2330" (TWSE), "3105" (TPEX), "GDX" (AMEX) exchange: Exchange — crypto: KUCOIN, BINANCE, MEXC; stocks: EGX, BIST, NASDAQ, NYSE, AMEX, NYSEARCA, PCX, SSE, SZSE, TWSE, TPEX timeframe: Time interval (5m, 15m, 1h, 4h, 1D, 1W)

Returns: A structured debate between 3 AI agents culminating in a final trading decision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
exchangeNoKUCOIN
timeframeNo15m
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds the debate structure and final trading decision output. No contradictions, but no additional disclosure of costs, rate limits, or other behaviors beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The main description is a single clear sentence, and the Args block is well-structured with examples. Every sentence adds value, though the Args block could be slightly more compact.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multi-agent debate, three parameters, no output schema), the description covers inputs with examples and explains the return value (structured debate with final decision). No missing critical details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description's Args block provides extensive examples for symbol (crypto and stock formats), exchange (full list of supported exchanges), and timeframe (concrete intervals). This adds significant meaning beyond the schema's bare types and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Run' and the resource 'multi-agent debate (Technical, Sentiment, Risk)' for a specific symbol. It distinguishes itself from sibling tools like market_sentiment or combined_analysis by explicitly naming the three-agent debate structure.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus siblings such as market_sentiment, combined_analysis, or multi_timeframe_analysis. The description only says 'for a specific symbol' but does not specify contexts or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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