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tedorigawa001

TradingView-MCP

classify_cross_asset_shocks

Classify EURUSD or USDJPY shocks by comparing them with DXY, US10Y, and XAUUSD movements at the same UTC time, returning only observed state without forward-looking signals.

Instructions

Classify observed EURUSD or USDJPY shocks after exact-time cross-asset collection. It temporarily uses one auxiliary chart for DXY, US10Y, and XAUUSD, restores it after each read, and applies the frozen same-UTC-slot baseline contract. It reports observed state only, never a forward outcome, candidate, order-flow claim, or trading instruction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
state_limitNoMaximum latest classified state rows to return. Aggregate counts use every eligible row. Default: 200
load_more_barsNoAdditional history to request for the target and each temporary context before reading. Default: 0
expected_timeframeYes
target_chart_indexYes
auxiliary_chart_indexYes
expected_target_symbolYes
minimum_classified_statesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.10

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and discloses meaningful behavior: it temporarily borrows an auxiliary chart, restores it after each read, applies a frozen same-UTC-slot baseline contract, and restricts output to observed state. This is substantial transparency about side effects and scope, though it does not explain what the returned classified state rows contain or whether the operation is idempotent.

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 description is compact and front-loaded with the core purpose, followed by key behavioral caveats. Every sentence contributes value, though the phrase 'frozen same-UTC-slot baseline contract' is jargon-heavy and could be clearer.

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

Completeness2/5

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

Given no output schema, no annotations, eight parameters, and low schema coverage, the description is not complete enough for correct invocation. It covers scope and chart side effects but leaves parameter semantics, output structure, and the meaning of 'classified state rows' undefined, so an agent cannot confidently determine all required inputs and expected result formatting.

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

Parameters2/5

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

Schema description coverage is only 25%, leaving important parameters like target_chart_index, auxiliary_chart_index, count, and minimum_classified_states without meaningful schema descriptions. The tool description adds some context by explaining that the auxiliary chart is used for DXY, US10Y, and XAUUSD, and that the target is EURUSD or USDJPY, but it does not compensate for the majority of undocumented parameters.

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 a specific action ('Classify observed EURUSD or USDJPY shocks') with a precise resource scope and method ('after exact-time cross-asset collection'). It also differentiates from siblings by explicitly saying it 'reports observed state only, never a forward outcome, candidate, order-flow claim, or trading instruction', which distinguishes it from related tools like evaluate_cross_asset_shock_outcomes.

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

Usage Guidelines4/5

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

The description communicates the intended context: use after exact-time cross-asset collection and for observed-state classification rather than forward-looking evaluation. However, it does not name sibling tools or explicitly state when to use alternatives like preflight_cross_asset_shock or evaluate_cross_asset_shock_outcomes, leaving some routing to inference.

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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