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GammaRips Options Intelligence

Contract Price Replay

replay_contract
Read-onlyIdempotent

Replay option price bars for any OCC contract to evaluate entry/exit rules. Select minute or daily bars, and set optional target/stop percentages to identify first-crossing signals.

Instructions

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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

The description reveals several behavioral traits beyond the readOnly/idempotent annotations: it does not simulate exits, it serves first-crossing sequences from the tape, minute paths have a specific engine-table fallback, tape is thin so absent bars are meaningful, and touch times are evidence rather than tick-perfect truth. These details materially shape how an agent interprets results.

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 organized with a clear lead sentence, two bulleted mode explanations, a data-caveat paragraph, and a structured Args list. Every sentence adds operational value, and the most important scoping information ('does NOT simulate or validate exits') is front-loaded. Despite its length, it is efficiently structured for a 7-parameter tool with dual modes.

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 description covers mode-specific behavior, parameter semantics, defaults, constraints, data-quality caveats, and explicitly disclaims investment advice. An output schema exists, so detailed return-structure documentation is not required from the description. There are no significant gaps that would prevent an agent from invoking 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 all parameter semantics. It delivers with an Args section that explains each of the 7 parameters, including required/optional status, defaults, format examples (e.g., OCC ticker, YYYY-MM-DD), mode-specific applicability, and behavior such as 'date is ignored' in day mode and the 120-day cap on from_date/to_date.

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 precise statement: 'Raw option price data for YOUR OWN entry/exit rule', then clarifies that the server does NOT simulate or validate exits and returns bars. It clearly identifies the resource (option price bars), the verb (replay/return), and the two granularity modes, making the tool's role unambiguous relative to simulation-type siblings.

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 explicit usage context for each granularity mode: minute for a single intraday session with an optional bracket, day for daily OHLCV to mark or replay a paper position. It also states exclusions: 'does NOT simulate or validate exits' and 'date is ignored' in day mode. However, it does not explicitly name sibling alternatives like get_signal or get_playbook, so the 'when-not-to-use' guidance is implied rather than directly referencing other tools.

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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