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Market sentiment

get_sentiment_data
Read-onlyIdempotent

Get market sentiment indicators: CBOE Put/Call ratios (total, equity, index, VIX), AAII investor sentiment survey (bull/bear/neutral %), and VIX level. Useful for contrarian signals at extremes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoWhich data: 'all' (default), 'put_call', 'vix'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
put_callNo

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds no additional behavioral context beyond listing the data points; it does not mention rate limits, freshness of data, or response format, meaning it adds marginal value over annotations alone.

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 two sentences and every sentence earns its place: the first identifies the data, the second gives an application hint. 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?

This is a simple read-only tool with one optional parameter, full schema coverage, and an output schema present. The description and annotations together are complete for an agent to select and invoke the tool correctly.

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

Parameters3/5

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

Schema coverage is 100% as the single 'type' parameter is fully described with an enum and default. The description lists the content but does not add syntax or selection guidance beyond what the schema already provides, so the baseline of 3 is appropriate.

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 states a specific verb ('Get') and a specific resource ('market sentiment indicators'), enumerating the exact data included (CBOE Put/Call ratios, AAII survey, VIX). While it doesn't explicitly contrast with sibling tools, the listed indicators make the tool's scope distinct from other market analysis 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?

It provides a clear use case ('useful for contrarian signals at extremes') but gives no explicit guidance on when not to use it or how to choose between the 'type' parameter values. It does not mention alternatives, which is acceptable for a simple tool but not fully explicit.

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

A4.2/5.0
Disambiguation5/5

Each tool maps to a distinct data category or function (prices, indicators, levels, sentiment, macro, crypto, intermarket, breadth, news, etc.). The few related tools are clearly separated by current vs. historical data, specific ratios vs. multi-lens overviews, or news lookup vs. news search.

Naming Consistency4/5

The majority of tools follow a consistent get_<noun> pattern with snake_case (e.g., get_price_history, get_technical_indicators). Two news tools use a public_ prefix instead, creating a minor but visible inconsistency.

Tool Count5/5

15 tools is within the ideal range for a market-data server and each tool covers a meaningful slice of the domain without redundancy. The count feels well-scoped for the server's purpose.

Completeness4/5

The tool surface is impressively broad, covering prices, indicators, sentiment, macro, crypto, intermarket analysis, news, and methodology. However, common data types like fundamentals (P/E, balance sheets) and options chains are absent, leaving a few potential user questions unanswered.

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