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0DTE Confluence

get_yield_curve

Delayed official FRED 10Y / 2Y / 2s10s.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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

A4/5.0
Behavior3/5

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

There are no annotations, so the description carries the behavioral burden. It does disclose useful behavioral context: the data is 'Delayed' and sourced from 'official FRED'. However, it does not mention units, update cadence, or whether 2s10s is a spread, leaving some behavioral ambiguity.

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 a compact, front-loaded phrase that uses every word meaningfully: delay status, source, and exact tenor composition. 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.

Completeness4/5

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

For a zero-parameter read-only tool with an output schema present, the description gives enough context: source, latency, and exact series. The only real gap is explicit usage routing, which was already penalized in usage guidelines, so the tool remains adequately specified for an agent to call it confidently.

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

Parameters4/5

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

The tool has zero parameters, so there is nothing for the description to clarify beyond the schema. This earns the baseline of 4; no parameter documentation is needed or expected.

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 names the exact financial resource: official FRED 10Y / 2Y / 2s10s yield curve data. Even though it lacks an explicit verb, the tool name 'get_yield_curve' plus this resource specificity makes the purpose unmistakable and distinct from sibling tools.

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

Usage Guidelines3/5

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

The description implies the tool should be used when the agent needs FRED 10Y/2Y/2s10s curve data, but it does not explicitly state when to use it versus alternatives or when not to use it. With many market-data siblings, some explicit routing guidance would strengthen this dimension.

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

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.

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