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ryansilk

ApexVol MCP Server

find_iv_opportunities

Detect extreme implied volatility using statistical thresholds and receive mean reversion strategy recommendations for selling or buying volatility.

Instructions

Find IV mean reversion trading opportunities.

Identifies when IV is statistically extreme (>2 std from mean) and suggests strategies to capture mean reversion.

Use this tool when the user asks about:

  • Mean reversion opportunities

  • Extreme IV levels

  • When to sell/buy volatility

  • IV statistical analysis

Args: ticker: Stock symbol z_score_threshold: Statistical threshold (default 2.0)

Returns: Opportunity assessment with strategy recommendations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYes
z_score_thresholdNo
Behavior3/5

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

With no annotations, the description carries the transparency burden. It discloses the statistical threshold (>2 std) and that it suggests strategies, but leaves out potential limitations, prerequisites, or specifics about the returned opportunity assessment beyond a vague 'strategy recommendations'.

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 with a clear first line, a bulleted usage list, Args/Returns sections, and no fluff. It is concise yet informative, with every sentence contributing to understanding.

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?

For a tool with 2 parameters and no output schema, the description covers purpose, usage, parameter semantics, and return type. It could be more complete by adding edge-case behavior or limitations, but it is sufficient for basic understanding.

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?

Given 0% schema coverage, the description compensates by explaining 'ticker' as 'Stock symbol' and 'z_score_threshold' as 'Statistical threshold' with a default of 2.0. This adds meaningful context that the schema alone lacks, though it could be more detailed (e.g., accepted values, behavior if threshold not met).

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 tool's purpose: finding IV mean reversion opportunities, with a specific method (statistical extremity >2 std) and action (suggests strategies). This distinguishes it from sibling tools like get_iv_rank or get_volatility_cone, which focus on measurement rather than opportunity detection.

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?

Explicitly lists when to use the tool (mean reversion opportunities, extreme IV, buy/sell volatility, IV statistical analysis), which provides clear context. Does not mention when-not-to-use or name alternatives, but the positive guidance is strong.

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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