get_historical_gexReplay gamma exposure (GEX) by strike at any minute since April 2018. Returns same shape as live /v1/exposure/gex. Alpha tier.
| Name | Required | Description | Default |
|---|---|---|---|
| at | Yes | As-of timestamp: YYYY-MM-DDTHH:mm:ss (ET) or YYYY-MM-DD (defaults to 16:00 ET) | |
| apiKey | No | FlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp. | |
| symbol | Yes | Stock/ETF ticker (e.g. SPY) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds context: the response shape matches the live endpoint, and it mentions 'Alpha tier' as an access-level signal. It does not disclose rate limits, pagination, or error behavior. The added context is useful but not extensive, consistent with the calibration standard where a read-only annotation lowers the burden.
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 three concise sentences, each earning its place: the first states the action and resource, the second clarifies the output format via the live endpoint reference, and the third notes the access tier. No redundant or filler content; front-loaded with the core verb 'Replay'.
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?
The tool is moderately complex with no output schema, but the description compensates by referencing the live /v1/exposure/gex shape. The input schema fully documents parameters, annotations declare read-only, and the time range and access tier are stated. Minor gaps remain (e.g., exact meaning of 'Alpha tier' and potential errors), but overall it is complete enough for an agent to select and invoke correctly.
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%, with detailed descriptions for all parameters: 'at' includes format and default time, 'apiKey' explains OAuth vs direct usage, and 'symbol' gives an example. The description itself adds no parameter-specific details, so the baseline of 3 applies because the schema carries the full semantic weight.
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 clearly states the tool's purpose: 'Replay gamma exposure (GEX) by strike' with a specific time range ('at any minute since April 2018'). It distinguishes from siblings by explicitly referencing the live counterpart: 'Returns same shape as live /v1/exposure/gex.' The verb 'Replay' and resource 'GEX' make the function unambiguous.
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 when to use this tool: for historical GEX replay by strike at a specific timestamp. It does not explicitly name alternatives or exclusion criteria, but the phrase 'same shape as live /v1/exposure/gex' implies the live endpoint is the alternative. The time range 'since April 2018' further clarifies applicability. Lacks explicit 'use get_gex for live' but context is sufficient.
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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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.