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risk_metrics

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Calculate advanced risk metrics including VaR, Sharpe ratio, Sortino ratio, Beta, and maximum drawdown for stocks and ETFs to assess investment risk and performance.

Instructions

Calculate advanced risk metrics: VaR, Sharpe, Sortino, Beta, Max Drawdown.

Professional-grade risk analysis for any stock or ETF. Returns Value-at-Risk (95%), Sharpe ratio (annualized), Sortino ratio, Beta vs benchmark, and maximum drawdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker (e.g., 'AAPL')
periodNoAnalysis period: 3mo, 6mo, 1y, 2y, 5y1y
benchmarkNoBenchmark ticker for beta calculationSPY

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations provide readOnlyHint=true, but the description adds valuable behavioral context beyond this: it specifies the exact metrics returned (VaR at 95%, annualized Sharpe ratio, etc.), which helps the agent understand the output format. However, it doesn't mention computational characteristics like performance or rate limits.

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 efficiently structured with two sentences: the first states the purpose and lists metrics, the second provides context and details the return values. Every sentence adds essential information with zero wasted words.

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?

Given the presence of annotations (readOnlyHint), 100% schema coverage, and an output schema (implied by context signals), the description provides complete context. It clearly explains what the tool does and what it returns, making it fully adequate for the agent's needs.

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?

With 100% schema description coverage, the schema already documents all three parameters thoroughly. The description doesn't add any additional parameter semantics beyond what's in the schema, so it meets the baseline score of 3 for adequate coverage without extra value.

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 specific action ('Calculate advanced risk metrics') and resources involved (VaR, Sharpe, Sortino, Beta, Max Drawdown for stocks/ETFs). It distinguishes itself from siblings like 'stock_quote' or 'technical_analysis' by focusing exclusively on risk metrics rather than price data or technical indicators.

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 implies usage context ('Professional-grade risk analysis for any stock or ETF') but doesn't explicitly state when to use this tool versus alternatives like 'portfolio_analysis' or 'compare_assets'. No explicit exclusions or comparisons to sibling tools are provided.

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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