get_advanced_volatilityGet advanced volatility analytics: SVI parameters, forward prices, total variance surface, arbitrage detection, greeks surfaces (vanna, charm, volga, speed), and variance swap fair values. Alpha tier required.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | No | FlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp. | |
| symbol | Yes | Stock/ETF ticker |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations declare readOnlyHint=true and the description does not contradict that. The description adds an auth requirement (Alpha tier) and enumerates the output categories, providing useful operational context beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the verb and purpose, followed by a dense but non-redundant list of deliverables and the access requirement. There is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description carries the burden of explaining return value categories, and it does list six output groups. However, it lacks detail on response shape, interpretation of SVI parameters, or time horizons, which is a meaningful gap for a complex analytics tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both apiKey and symbol, so the baseline is 3. The description does not add parameter-specific syntax or format details, but the schema already documents the two parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' and a clear resource 'advanced volatility analytics', then enumerates concrete deliverables: SVI parameters, forward prices, total variance surface, arbitrage detection, greeks surfaces, and variance swap fair values. This clearly distinguishes it from siblings like get_volatility and get_svi_params.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only usage signal is 'Alpha tier required', which is a prerequisite rather than a when-to-use guideline. There is no explicit mention of when to prefer this tool over alternatives like get_svi_params or get_volatility, so usage context is only implied by the word 'advanced'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping scopes: get_stock_summary, get_volatility, get_vrp, and get_exposure_summary all return comprehensive analytics with shared metrics, making it hard to pick the right one. The flow family (get_flow_live, get_flow_summary, get_flow_scan, get_flow_signals, etc.) has significant redundancy — get_flow_live bundles data also available via separate tools.
Tool names mostly follow a consistent get_<noun> pattern, with clear subgroups like get_historical_* and get_*_exposure. Minor deviations exist: post_screener, post_structure_pnl, calculate_greeks, and solve_iv break the get_ convention, but they are still predictable and readable.
With 73 tools, this is far beyond the 3–15 tool sweet spot and even the 50+ extreme mismatch threshold. While the domain is broad, the enormous surface is bloated by near-duplicate historical replay variants (18 get_historical_* tools) and multiple overlapping summary endpoints, making it unwieldy for an agent.
The tool set provides thorough coverage of options analytics: quotes, chains, greeks, volatility surface, VRP, exposure, flow, historical replay, screening, and strategy analysis. There are no obvious dead ends — core workflows like calculating greeks, getting exposure, and screening the universe are all supported.