get_historical_dexReplay delta exposure (DEX) by strike at any minute since April 2018. 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 |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / apiKey / defaultAdded value: +nullInput schema / properties / apiKey / descriptionPrevious value: -"Your FlashAlpha API key (Alpha tier)"New value: +"FlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp."Input schema / properties / apiKey / typePrevious value: -"string"New value: +[
+ "string",
+ "null"
+]Input schema / requiredPrevious value: -[
- "symbol",
- "apiKey",
- "at"
-]New value: +[
+ "symbol",
+ "at"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, and the description adds the replay/time-range scope. It doesn't contradict annotations, but it omits behavioral details such as response format, pagination, or implications of the 'Alpha tier' status. With annotations covering safety, this is adequate but not rich.
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?
Two short sentences with no redundant wording. The first sentence captures the core function and scope; the second adds a brief caveat. Every word earns its place.
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 the tool's simplicity, three well-documented parameters, and read-only annotation, the description is largely complete. It covers purpose and time scope, but could optionally describe the return format or clarify what 'Alpha tier' implies operationally. Minor gaps, not critical.
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?
Schema description coverage is 100%, so the input schema fully documents symbol, at, and apiKey. The description adds minor context like 'by strike' and 'any minute', but these are largely implicit in the schema and do not materially enhance parameter understanding.
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?
Description uses a specific verb ('Replay') and identifies the resource ('delta exposure (DEX) by strike') plus temporal scope ('since April 2018'). This clearly differentiates it from current DEX (get_dex) and other historical metric tools like get_historical_gex.
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 temporal phrase 'since April 2018' and verb 'Replay' imply historical retrieval, providing clear context. However, it doesn't explicitly state when to prefer this over sibling tools such as get_dex or other historical variants, nor mention any alternatives.
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.