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PantherWatch

panther-mcp

Official
by PantherWatch

tool_run_portfolio_backtest

Run a portfolio backtest with weighted asset allocations to evaluate how a trading strategy performs across diversified holdings.

Instructions

Run a portfolio backtest across multiple assets with weighted allocation.

Test how a strategy performs across a diversified portfolio. Each asset gets a weighted allocation of the total capital.

assets: List of asset allocations. Each has:

  • symbol: Asset symbol (e.g. "BTC/USDT", "ETH/USDT")

  • weight: Portfolio weight from 0 to 1. All weights must sum to 1.0.

Example: [{"symbol": "BTC/USDT", "weight": 0.6}, {"symbol": "ETH/USDT", "weight": 0.4}]

The same strategy is applied to all assets. Returns a portfolio_backtest_id. Use get_portfolio_backtest_status to poll, then get_portfolio_backtest_results for results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetsYes
end_dateNo
strategyYes
timeframeYes
commissionNo
start_dateYes
initial_cashNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does a good job: it discloses the async pattern, explains that a portfolio_backtest_id is returned, and instructs polling for status then fetching results. It also clarifies that the same strategy is applied across all assets. Minor omissions like validation of weight sums or side effects are not disclosed, but the key behavior is covered.

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 well-structured and appropriately sized: an opening sentence, a short explanation, a bulleted asset spec, a concrete example, and the follow-up workflow. It is front-loaded and every section contributes useful information without filler.

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?

Despite strong asset documentation and a clear workflow, the description is not complete enough for a complex 7-parameter tool with nested objects and no annotations. The required strategy object is undocumented, date/timeframe formats are missing, and optional parameter semantics are not explained. An agent cannot confidently construct a full valid request without additional context.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It meaningfully documents the assets parameter with symbol, weight, the sum-to-1.0 constraint, and an example. However, the strategy parameter is essential but left completely opaque, and timeframe, start_date, end_date, commission, and initial_cash receive no explanatory attention.

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: running a portfolio backtest across multiple assets with weighted allocation. It clearly distinguishes itself from single-asset backtest siblings by emphasizing multiple assets, weights, and the same strategy applied to all assets.

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

Usage Guidelines3/5

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

The description gives clear context for the multi-asset portfolio use case and the follow-up workflow (poll status, fetch results). However, it never explicitly contrasts this with tool_run_backtest or states when to choose one over the other, so the usage guidance is implied rather than explicit.

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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