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Get Historical Coverage

get_historical_coverage
Read-only

List symbols backfilled in the historical archive with coverage windows, day counts, and gaps. Call this first to check whether a symbol + date range is queryable before sending a replay request. Alpha tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyNoFlashAlpha API key. Omit when calling via /mcp-oauth (OAuth flow); required on /mcp.
symbolNoOptional symbol filter (e.g. SPY) - omit for all covered symbols

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses that this is a read-only listing operation (consistent with readOnlyHint: true) and adds pragmatic context about the functional behavior: it returns coverage windows, day counts, and gaps and is meant as a pre-flight check. 'Alpha tier' flags potential instability, which is useful 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, all informative. The first sentence states the action, the second gives usage guidance, and the third notes the alpha tier. No redundant text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the lack of an output schema, the description tells the user what to expect (symbols, coverage windows, day counts, gaps) and how to use it. The main gaps are minor – e.g., no explicit mention of pagination or error semantics – but given the tool's simplicity and the schema coverage, it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides thorough descriptions for both parameters (apiKey and symbol) at 100% coverage, so the description does not need to add parameter-level details. It implies filtering by symbol but leaves the schema to handle specifics, as per the baseline for high schema coverage.

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?

The description opens with a specific verb and resource: 'List symbols backfilled in the historical archive with coverage windows, day counts, and gaps.' It also states its role relative to other historical data tools ('Call this first...'), distinguishing it from siblings like get_historical_stock_quote.

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

Usage Guidelines4/5

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

The second sentence explicitly states when to use this tool: 'Call this first to check whether a symbol + date range is queryable before sending a replay request.' This provides clear context, though it does not name alternatives or explicit when-not cases.

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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TDQS

A3.6/5.0
Disambiguation2/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness5/5

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.

Resources