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78degrees

QuantRisk-MCP-Server

performance_attribution

Decompose portfolio returns into factor exposures, sector allocation, and position contributions. Compute risk-adjusted metrics including Sharpe, Sortino, and Information ratios.

Instructions

Break down portfolio performance into factor exposures, sector allocation, and position contributions. Computes Sharpe, Sortino, Treynor, Calmar, and Information ratios.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
positionsYesArray of portfolio positions. Free tier: max 20 positions (basic ratios only). Paid tier: up to 500 positions with full factor attribution.
period_daysNoMeasurement period in trading days. 252 = ~1 year. Range: 30-1260. Default: 252.
benchmarkNoBenchmark ticker for relative performance metrics (Information Ratio, Tracking Error, Beta). Default: SPY.SPY
risk_free_rateNoAnnualized risk-free rate as a decimal, e.g. 0.05 = 5%. Used in Sharpe, Sortino, and Treynor ratios. Default: 0.05.
Behavior2/5

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

No annotations provided, so description should disclose behavioral traits. It mentions tier limitations but not auth needs, mutability, rate limits, or side effects. The output format is not described.

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?

Two sentences, front-loaded with core purpose, then specific ratios. No fluff. Every sentence adds value.

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 4 parameters and no output schema, description should explain expected outputs and behavioral scope. It does not cover return values, factor methodology, or what 'full factor attribution' entails. Leaves significant gaps for agent invocation.

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 coverage is 100%, so baseline is 3. Description adds minor context (e.g., free/paid limits on positions) but largely restates what schema descriptions already provide. No new semantics beyond schema.

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

Purpose4/5

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

The description clearly states it breaks down portfolio performance into factors, sectors, and contributions, and lists specific ratios. It differentiates itself from generic analysis tools but doesn't explicitly contrast with siblings like compare_portfolios.

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. Does not mention prerequisites, when not to use, or alternatives. The tier limitation is noted but not in the context of decision-making.

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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