Skip to main content
Glama

veroq_social_trending

Discover trending tickers and topics on social media platforms like Reddit and Twitter/X to identify what retail investors are discussing in real-time.

Instructions

Get tickers and topics currently trending on social media across Reddit, Twitter/X, and other platforms.

WHEN TO USE: To discover what retail investors are buzzing about right now. No parameters needed. RETURNS: Trending symbols with name, mention count, sentiment score, and 1-hour change in mentions. COST: 2 credits. EXAMPLE: {}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries full disclosure burden effectively. It reveals COST ('2 credits'), data sources ('Reddit, Twitter/X'), temporal scope ('currently trending', '1-hour change'), and return structure ('name, mention count, sentiment score'). Missing rate limits or caching details, but cost transparency is critical for API tools.

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?

Excellent structured format with clear section headers (WHEN TO USE, RETURNS, COST, EXAMPLE). Every line delivers value. Front-loaded with core purpose, followed by operational metadata. No wasted words despite covering multiple dimensions of tool behavior.

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?

Despite lacking an output schema, the description compensates with a detailed RETURNS section documenting specific fields (mention count, sentiment score, 1-hour change). Combined with cost and usage context, this provides complete information needed for an agent to invoke the tool correctly and handle its output.

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?

Input schema has 0 parameters, establishing a baseline of 4. The description confirms this with 'No parameters needed' and provides 'EXAMPLE: {}', which validates the empty schema structure and prevents confusion about missing parameters.

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 uses a specific verb ('Get') with clear resources ('tickers and topics') and scope ('trending on social media across Reddit, Twitter/X'). It effectively distinguishes from siblings like 'veroq_trending' (likely market data) and 'veroq_social_sentiment' (likely requires specific ticker input) by emphasizing discovery of trending content across platforms.

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

Usage Guidelines4/5

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

Provides explicit 'WHEN TO USE' guidance ('To discover what retail investors are buzzing about right now') and notes 'No parameters needed.' Lacks explicit 'when-not' guidance or named alternatives (e.g., contrast with veroq_social_sentiment for specific ticker analysis), but the contextual use case is clearly defined.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Veroq-ai/veroq-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server