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TradingView-MCP

run_strategy_experiment

Compare baseline and candidate Pine strategies on the active chart by running a bounded Strategy Tester experiment that returns metric deltas without placing orders.

Instructions

Run one bounded baseline-versus-candidate Strategy Tester experiment on the active chart. Both variants are resolved to exact saved Pine versions, applied serially with optional input overrides, bound to full-ledger SHA-256 ids, and removed after collection. Returns metric deltas without a synthetic score. Without confirm=true it only previews the experiment. It never places orders.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNoMust be true to temporarily add strategies and run the experiment. Default: false
baselineYes
candidateYes
minimum_tradesNoClosed trades required per variant. Default: 30
expected_symbolYesExact active-chart symbol, e.g. OANDA:USDJPY
expected_timeframeYesExact active-chart timeframe, e.g. 240 or 1D

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.10

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral disclosure burden, and it does so thoroughly. It explains that strategies are temporarily added, resolved to exact saved Pine versions, applied serially, bound to full-ledger ids, removed after collection, and that the tool never places orders. This gives an agent a clear safety and side-effect profile.

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

Conciseness5/5

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

The description is four sentences with no filler. It front-loads the core purpose, then provides constraints, cleanup behavior, output characteristics, preview semantics, and a critical safety guarantee. Every sentence contributes meaningful information.

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

Completeness5/5

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

Despite having no output schema, the description adequately covers outputs ('Returns metric deltas without a synthetic score'), execution requirements, cleanup, and the confirm prerequisite. The tool is complex with nested objects, but the description gives enough context for an agent to understand what happens and what to expect.

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

Parameters4/5

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

Schema coverage is 67%, and the description adds meaning beyond the schema by explaining baseline-versus-candidate semantics, optional input overrides, exact saved Pine version resolution, and the confirm gate. It does not fully describe every parameter, but it enriches the less-documented nested baseline/candidate objects and the overall experimental flow.

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 states a specific verb and resource: 'Run one bounded baseline-versus-candidate Strategy Tester experiment on the active chart.' It clearly distinguishes this tool from siblings like run_backtest or run_strategy_walk_forward by emphasizing the comparison structure, boundedness, and absence of a synthetic score.

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 provides clear usage context, especially the preview-versus-execute distinction: 'Without confirm=true it only previews the experiment.' It also gives safety guidance by stating 'It never places orders.' It does not explicitly name sibling alternatives or when-not-to-use conditions, so it stops short of a 5.

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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