Skip to main content
Glama

0DTE Confluence

get_skew

IV smile / skew strip + wing-fattening flag from Tradier chain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoSPY

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It does disclose a meaningful trait: the data is derived 'from Tradier chain' and includes a flag, which hints at source and derived nature. However, it does not mention permissions, rate-limit behavior, failure modes, or whether any state is written; the 'get' verb softens this gap, but the description itself is light on behavioral guarantees.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is a single dense sentence with no filler; it names the output components and the data source in under a dozen words. It is appropriately short for a simple tool, though it could be slightly clearer with an explicit verb and a usage hint.

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

Completeness2/5

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

Given no annotations and an output schema presumably covering return fields, the description still leaves selection guidance completely unaddresed. An agent must guess whether this tool is appropriate for skew/flattening analysis versus related options-structure tools, and there is no mention of common edge cases or how the flag should be interpreted.

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

Parameters2/5

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

Schema coverage is 0% and the single 'symbol' parameter has no description. The description does not explain how the symbol maps to the skew computation or what values are expected, and the default of SPY is the only semantic hint. While the parameter is simple and self-evident, the description still fails to compensate for the missing schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Naming the tool is 'get_skew' but the description gives a concrete domain outcome: an IV smile/skew strip plus a wing-fatening flag sourced from a Tradier chain. It clearly identifies the analytical object and distinguishes it from other get_* siblings such as GEX profiles or correlation grids, even though it lacks an explicit verb.

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

Usage Guidelines2/5

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

The description gives no guidance on when to choose this tool over alternatives like get_pin, get_rails, or get_gex_profile. There are no stated conditions, use cases, or exclusions; an agent must infer that skew analytics is the intended use because of the name and description alone.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3/5.0
Disambiguation5/5

Each tool targets a distinct metric or workflow—alert checks, alert lists, gamma maps, volatility indices, replay timelines, execution plans—so an agent can reliably pick the right one from its description. Even the alert-related tools (get_latest_alert, list_alert_history, check_alert_tradeable) have clearly separate outputs.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (mostly get_, plus check_, format_, list_, plan_). This makes the set predictable and easy to scan.

Tool Count2/5

At 32 tools, the surface is heavy and approaches a disorganized collection of endpoints rather than a curated set. Many individual get_* indicators could be grouped into a smaller number of dashboard or snapshot tools without losing clarity.

Completeness4/5

The server covers the core 0DTE intelligence lifecycle: alerts, historical replays, risk overlays, structure, gamma, volatility, news, and advisory planning. Minor gaps exist—such as a direct quote or option chain feed—but they are not essential to the stated purpose.

Resources