get_historical_surfaceReplay the implied volatility surface grid at any minute since April 2018. EOD-stamped (SVI parameters refresh daily). Alpha tier.
| Name | Required | Description | Default |
|---|---|---|---|
| at | Yes | As-of timestamp: YYYY-MM-DDTHH:mm:ss (ET) or YYYY-MM-DD | |
| 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 readOnlyHint annotation already establishes safety. The description adds meaningful behavioral details: EOD-stamped data, SVI parameters refreshing daily, and an April 2018 availability start, which are beyond annotation info.
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 concise (three short fragments) and front-loaded with the core action. Every fragment adds distinct information: purpose, data cadence, access tier.
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?
Given no output schema, the description covers scope, time range, data frequency, and access tier. It does not detail the exact grid structure returned, but the purpose and constraints are well specified for a moderate-complexity 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?
All 3 parameters are fully described in the schema (100% coverage), so baseline is 3. The description adds semantic value for the 'at' parameter by noting EOD-stamped and daily SVI refresh, informing how the timestamp is interpreted.
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 the specific verb 'Replay' with the resource 'implied volatility surface grid' and specifies a clear time scope ('any minute since April 2018'). This clearly distinguishes it from sibling tools like get_surface (current) and other historical getters.
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 description provides clear context for historical IV surface retrieval via 'Replay' and the date range. It does not explicitly name alternatives or exclusions, but the usage context is unmistakable, fitting the 'clear context, no exclusions' level.
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.