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DeepFusion MCP Server

data_juglar_extended

Get Juglar cycle data from FRED since 1929, including non-residential fixed investment, private fixed investment, GNP, and capacity utilization as annual JSON arrays for investment-cycle analysis.

Instructions

朱格拉周期 FRED 扩展版(1929~),非住宅固定投资+私人固投+GNP+产能利用率,年频JSON数组

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses the data source, time period, frequency (annual), and output format (JSON array), which are useful. However, it does not explain what 'extended' adds over the base version, nor any caveats about data completeness or how missing values are handled.

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 single compact sentence that front-loads the core identity (Juglar cycle FRED extended version), then lists the included indicators, frequency, and output format. Every phrase carries information, with no filler or redundancy.

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 data-retrieval tool with an output schema, the description covers the essential invocation context: source, period, indicators, frequency, and format. It is slightly incomplete in not clarifying the exact difference between the extended and non-extended versions, but this is a minor gap.

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 no parameter semantics gap. The baseline of 4 applies because no parameter documentation is needed; the description instead conveys the data content, which is the only meaningful semantic information for invoking this tool.

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?

The description clearly identifies the resource as the extended Juglar cycle dataset from FRED and specifies its content (non-residential fixed investment, private fixed investment, GNP, capacity utilization). The 'extended' qualifier and the period '1929~' help distinguish it from the plain data_juglar sibling, though no explicit action verb like 'retrieves' is present.

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?

No explicit guidance is given about when to use this tool versus alternatives such as data_juglar, data_kitchin_extended, or chart_juglar_cycle. The name and content imply use for extended FRED-based Juglar cycle data, but there is no clear when-to-use or when-not-to-use statement.

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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