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get_iv_radar

Retrieve implied volatility rank, percentile, and regime for a stock to evaluate whether options are cheap or expensive relative to historical norms.

Instructions

Retrieve implied-volatility (IV) metrics for a single stock.

Use this tool when:

  • You need to assess whether options are cheap or expensive relative to historical norms (IV rank / IV percentile).

  • You want the current volatility regime ("Low", "Normal", "Elevated", "Extreme") to frame risk sizing or strategy selection.

  • You are analyzing skew or risk-reversal direction (put-heavy vs call-heavy market).

Do NOT use this tool if you already called analyze_stock — the IV data is included in that response.

Parameters

symbol : str Exchange ticker in uppercase, e.g. "TSLA", "NVDA", "IWM".

Returns

dict with keys: symbol : str — normalized ticker atm_iv : float — at-the-money implied volatility (annualized %) iv_rank : float — 0–100; ≥80 = expensive, ≤20 = cheap iv_percentile : float — historical percentile (0–100) risk_reversal : float — 25-delta risk reversal (positive = call-skew) volatility_regime: str — "Low" | "Normal" | "Elevated" | "Extreme"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
Behavior4/5

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

No annotations exist, but description compensates by detailing the output and purpose. It is a read-only data retrieval tool, but does not explicitly state that it is non-destructive; still clear enough.

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?

Well-organized into purpose, usage, parameters, and returns sections. Every sentence adds value; no fluff.

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?

For a simple retrieval tool with one parameter and no output schema, the description fully covers purpose, usage, parameter, and return values, and explicitly distinguishes from sibling tool analyze_stock.

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?

Schema coverage is 0%, but description includes a dedicated Parameters section explaining the symbol parameter with examples ('TSLA', 'NVDA', 'IWM') and format requirements (uppercase).

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?

Clearly states 'Retrieve implied-volatility (IV) metrics for a single stock', with specific verb and resource. Distinguishes from sibling tool analyze_stock by noting it already includes IV data.

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

Usage Guidelines5/5

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

Provides explicit when-to-use scenarios (assess cheap/expensive, volatility regime, skew analysis) and a do-not-use condition (if already called analyze_stock).

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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