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DevDizzle

GammaRips Options Intelligence

Signal Detail

get_signal
Read-onlyIdempotent

Retrieve an enriched options signal for a ticker: thesis, catalyst, recommended contract, and point-in-time features. For earnings risk, check if the next earnings date falls within an option's expiration window.

Instructions

Deep dive on a single ticker/contract. Two `view`s:

  * view="detail" (DEFAULT) — the full enriched signal for one ticker:
    thesis, catalyst, the recommended contract, and point-in-time
    features (leakage-safe view). `full=true` includes the long narrative
    (news_summary, flow_intent_reasoning). If the ticker isn't in the
    pool for the date, the error lists the dates on which it does appear.
  * view="earnings" — the doctrine earnings-window check (RM-003): the
    next scheduled earnings date and whether it lands ON OR BEFORE the
    contract expiration (`earnings_in_window`). The engine applies this
    rail only at its own pick time, NOT in the pool, so pool rows CAN
    carry earnings-window names — check every candidate yourself. Pass
    the pool's `recommended_contract` and both ticker and expiration are
    derived. FAIL-CLOSED: unknown date -> earnings_in_window=null, treat
    as in-window.

Args:
    ticker: underlying symbol (required for detail; optional for earnings
        if `contract` is given).
    view: "detail" (default) | "earnings".
    scan_date: detail only — YYYY-MM-DD (default: latest for the ticker).
    full: detail only — include the long narrative fields.
    expiration: earnings only — option expiration YYYY-MM-DD to test.
    contract: earnings only — OCC ticker supplying ticker+expiration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNo
viewNodetail
tickerNo
contractNo
scan_dateNo
expirationNo

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?

Annotations already declare readOnly, idempotent, and non-destructive. The description adds substantial behavioral context beyond that: fail-closed behavior for unknown earnings dates, leakage-safe point-in-time features, the engine applying earnings rails only at pick time, and the error listing alternate dates when a ticker is not in the pool. None of this contradicts the annotations.

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 well-organized with a brief lead sentence, labeled views, and an Args block. It is detailed but every sentence adds necessary information such as defaults, fail-closed semantics, or leakage safety. No filler or redundancy.

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 6 parameters, two modes, zero schema descriptions, and subtle behavioral rules, the description covers everything an agent needs to invoke it correctly: parameter semantics, defaults, edge cases, derivation rules, and error behavior. Since an output schema exists, not detailing return values is acceptable.

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 carries the full burden. It compensates thoroughly: each parameter is explained with defaults, required/optional status, view restrictions, and derivation rules (e.g., 'contract' supplying both ticker and expiration). This is far beyond what the bare schema provides.

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: 'Deep dive on a single ticker/contract.' It then enumerates two distinct views with concrete outputs, making the tool's purpose unambiguous and clearly distinguishable from sibling list/dashboard 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 detailed context for choosing 'detail' vs 'earnings', including defaults, derived parameters, and the important instruction to check every candidate yourself because pool rows can carry earnings-window names. However, it does not explicitly contrast with sibling tools, so the 'when to use vs alternatives' aspect is left mostly to inference.

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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