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ryansilk

ApexVol MCP Server

Stress Tests

generate_stress_tests
Read-only

Run stress tests on a portfolio under extreme market conditions like crashes, volatility spikes, and rallies to reveal potential P&L impacts and worst-case outcomes.

Instructions

Run stress test scenarios on a portfolio.

Tests portfolio under extreme market conditions like crashes, vol spikes, and rallies.

Use this tool when the user asks about:

  • Stress testing

  • Crash scenarios

  • Worst-case analysis

Args: positions: JSON array of positions, e.g. '[{"ticker": "AAPL", "position_type": "STOCK", "quantity": 100, "current_price": 210}, {"ticker": "AAPL", "position_type": "CALL", "quantity": -2, "strike": 220, "expiration": "2026-08-21", "current_price": 4.10, "delta": 0.31, "theta": -8.2, "vega": 21.0}]'. Get option Greeks from get_options_chain first. Plain text ("AAPL 100 shares") works for stock-only portfolios.

Returns: P&L under various stress scenarios

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
positionsYes

Schema Changelog

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

  1. First observedv0.1.1

TDQS

A4.3/5.0
Behavior4/5

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

The description adds context beyond the readOnlyHint annotation by explaining that it runs simulations and returns P&L under stress scenarios. This helps the agent understand the tool's non-mutating, analytical nature and its output.

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 front-loaded. It opens with a clear purpose, then provides usage triggers, input format details, and output summary. Every sentence adds value, with no redundancy or filler.

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

Completeness4/5

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

The description is fairly complete for a single-parameter tool: it covers input format, example, dependency on get_options_chain, and output (P&L under scenarios). It could list specific stress scenarios, but the examples given (crashes, vol spikes, rallies) suffice for most use cases.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by providing a detailed JSON example, explaining the expected position format, including option Greeks, and noting that plain text works for stock-only portfolios. This is excellent parameter guidance.

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 the tool 'Run stress test scenarios on a portfolio' and explains extreme market conditions like crashes, vol spikes, and rallies. It does not explicitly distinguish from similar sibling tools like run_scenario_analysis, but the purpose is specific and actionable.

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 explicitly provides when-to-use scenarios (stress testing, crash scenarios, worst-case analysis). It does not mention when not to use it or alternatives, but gives clear usage context and even a prerequisite (get option Greeks from get_options_chain first).

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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