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GammaRips Options Intelligence

by io.github.DevDizzle

Contract Price Replay

replay_contract
Read-onlyIdempotent
Raw option price data for YOUR OWN entry/exit rule. This server does NOT
simulate or validate exits — it returns bars (the RM-002/RM-004 boundary).
Two `granularity` modes:

  * granularity="minute" (DEFAULT) — the intraday minute path for one
    session (`date` required). Optionally pass a bracket (target_pct/
    stop_pct, PERCENT of the 10:00 ET anchor) and the response also reports
    the exact FIRST-CROSSING sequence measured from the tape. Pool
    excursion windows are served from the engine's minute-path table;
    anything else falls back to an upstream minute fetch.
  * granularity="day" — the DAILY mark series (OHLCV) over a date range,
    to mark a live paper position day by day or replay a closed one. Uses
    `from_date`/`to_date` (span capped at 120 days); `date` is ignored.

Option tape is THIN — minutes/days with no prints have no bar; treat
touch times as evidence, not tick-perfect truth. Paper-trade research
data; not investment advice.

Args:
    contract: OCC option ticker (e.g. "O:UNIT260717C00030000").
    date: minute mode — ET session date YYYY-MM-DD (required).
    granularity: "minute" (default) | "day".
    target_pct: minute mode — optional +X% level for first-crossing.
    stop_pct: minute mode — optional -Y% level for first-crossing.
    from_date: day mode — start YYYY-MM-DD (default: 30d before to_date).
    to_date: day mode — end YYYY-MM-DD inclusive (default: today ET).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
to_dateNo
contractYes
stop_pctNo
from_dateNo
target_pctNo
granularityNominute

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses important behavioral traits: no exit simulation/validation, reliance on RM-002/RM-004 boundary bars, first-crossing reporting, fallback to upstream minute fetch, and the thin tape caveat that missing bars are not evidence of no activity. This gives an agent realistic expectations about data quality and return semantics.

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 detailed but well-structured with front-loaded purpose, mode bullets, a critical data-quality caveat, and an organized Args list. Every section contributes to correct invocation or interpretation of results; there is no filler or redundant restating of the schema.

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?

For a tool with seven parameters and no schema-level descriptions, the description is remarkably complete. It covers mode selection, parameter defaults and constraints, ignored parameters, output expectations (bars, first-crossing sequence, OHLCV), and data reliability caveats. Since an output schema is reported to exist, the description does not need to enumerate return fields.

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?

Even though schema description coverage is 0%, the description's Args section fully compensates by explaining each parameter: contract format, date requirements, granularity modes, target_pct/stop_pct meaning relative to the 10:00 ET anchor, and from_date/to_date defaults. It also clarifies that date is ignored in day mode, which is not inferable from the schema alone.

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 clearly identifies the resource (raw option price bars) and the operation (replay for a user's own entry/exit rule). It distinguishes itself from simulation/validation tools by explicitly stating this server does NOT simulate or validate exits. The two granularity modes further define its scope, making it unambiguous against sibling get_* tools.

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 gives clear context for when to use each granularity mode: minute for a single session with a required date, and day for marking live or closed paper positions over a date range. It also flags limits such as the 120-day span and thin tape. It does not explicitly name alternative sibling tools or say when not to use this tool, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All GammaRips Options Intelligence toolsInspect
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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.

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