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GammaRips Options Intelligence

by io.github.DevDizzle

Market Calendar Status

get_market_calendar_status
Read-onlyIdempotent
Market-calendar reference. Two `view`s:

  * view="status" (DEFAULT) — is the US equity market open today, plus the
    next open/close, holiday, and early-close flags (NYSE calendar,
    deterministic — no "is the market open?" hallucination).
  * view="scan_dates" — which recent scan dates have GammaRips data, with
    per-date signal counts (the pool's data-availability calendar).

Args:
    view: "status" (default) | "scan_dates".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewNostatus

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond annotations: it states the status view is deterministic and intentionally avoids hallucination about market open status, and it describes what each view returns. This gives the agent confidence in the tool's behavior and outputs.

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 compact and well-structured, with a short overview followed by bullet points for each view and an explicit Args section. Every sentence adds useful information, and the most important distinction (the two views) is front-loaded.

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

Completeness5/5

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

The tool has minimal complexity with a single optional parameter and no output schema, but the description covers the purpose, both modes, their outputs, defaults, and the deterministic guarantee. Nothing essential is missing for an agent to select and invoke the tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must carry the parameter documentation burden. It does so effectively by enumerating the only parameter 'view' with its two allowed values, the default 'status', and a distinct explanation of what each value returns. This fully compensates for the lack of schema-level parameter descriptions or enums.

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 explicitly identifies the tool as a market-calendar reference and details the two views: 'status' for US equity market open status plus next open/close, holiday, and early-close flags, and 'scan_dates' for data-availability calendar with per-date signal counts. This is specific and distinguishes the tool from sibling data-retrieval tools by naming the resource it references.

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 description clearly implies when to use each view: use 'status' to check if the US equity market is open, and use 'scan_dates' to find which recent scan dates have GammaRips data. It does not explicitly name alternative sibling tools or state when not to use this tool, but the intended usage context is clear.

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

A4.7/5.0
Disambiguation5/5

Each tool owns a clearly distinct surface: reports, liquidity, market calendar, methodology, pool data, regime context, per-ticker signals, outcome research, and raw price replay. Even the closest neighbors (get_pool, get_signal, get_daily_report) are separated by pool-wide versus single-ticker versus report granularity, and the view parameters remove ambiguity.

Naming Consistency4/5

Seven tools follow a consistent get_<noun> pattern, while query_outcomes and replay_contract deviate with a different verb style. All names are snake_case and predictable, so this is a minor inconsistency rather than chaotic naming.

Tool Count5/5

Nine tools is well within the ideal range for an intelligence and research server. Each tool earns its place, covering a distinct part of the workflow without bloat or thinness.

Completeness5/5

The toolset covers the full research workflow: market/reference context, methodology, candidate pool, live liquidity, per-ticker signals, regime context, outcome research, and raw price replay for custom exit rules. There are no obvious dead ends or missing lifecycle steps for the server's stated purpose.

Resources