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ZENITH Code

Fear & Greed index

get_fear_greed_index
Read-only

Current market sentiment score (0-100) with label (Extreme Fear … Extreme Greed), previous close, one-month-ago score and components. ZENITH Code proprietary volatility-based composite. Fear & Greed スコア(自社計算)。 Date-times are ISO 8601 UTC (YYYY-MM-DDTHH:MM:SSZ; add 9 hours for Japan time). Date-only fields are YYYY-MM-DD. 時刻(日時)は ISO 8601 の UTC(YYYY-MM-DDTHH:MM:SSZ。日本時間は 9 時間を足す)。日付だけの項目は YYYY-MM-DD。

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds genuinely useful context about what the score is (a proprietary volatility-based composite, not a standard published index) and what fields come back, but it says nothing about refresh cadence, update frequency, or licensing/limits.

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

Conciseness3/5

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

The return-content sentence is front-loaded and earns its place, but the remainder is largely duplicated boilerplate: the Japanese restatement of the score name and a two-language ISO 8601 date-format note that is irrelevant to a zero-parameter tool whose described outputs contain no date fields. Roughly half the text is noise for this specific tool.

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?

With no output schema and no parameters, the description must carry the return shape, and it does: numeric score, qualitative label range, previous close, one-month-ago comparison, and components. The only shortfall is that 'components' is unspecified — an agent cannot tell how many sub-indicators or what they are named.

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 takes zero parameters, so there is no parameter semantics to explain and the baseline applies. Nothing in the description misleads about inputs.

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 names a specific resource (current market sentiment score 0-100) and enumerates the payload: label, previous close, one-month-ago score, and components. That is enough to separate it from sibling metrics like get_market_breadth or get_sector_performance, though it never names an alternative explicitly to sharpen the distinction.

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?

There is no explicit when-to-use statement, no exclusions, and no pointer to sibling tools such as get_market_breadth or get_technical. Usage is only implied by the phrase 'Current market sentiment score', which an agent can infer, but the definition does nothing to route the agent among alternatives.

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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