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veroq_trending

Identify people, organizations, and topics with the highest mention volume in the past 24 hours. Get their name, type, ticker, and mention count to discover current news dominance and guide research.

Instructions

Get trending entities — people, orgs, and topics with the most mentions in the last 24 hours.

WHEN TO USE: To discover what's dominating the news cycle right now. Good starting point for research. RETURNS: Array of entities with name, type, ticker (if applicable), and 24h mention count. COST: 1 credit. EXAMPLE: { "limit": 10 }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax entities to return
Behavior4/5

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

No annotations provided, so the description carries the full burden. It discloses the time window (24h), return format, cost (1 credit), and example. It does not mention idempotency or side effects, but as a read-only data retrieval tool, the description is sufficiently transparent.

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 well-structured with clear sections (purpose, when to use, returns, cost, example) in only five sentences. Every sentence adds value with no redundancies.

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?

For a simple tool with one optional parameter and no output schema, the description covers all necessary aspects: what it does, when to use, return structure, cost, time frame, and an example. It is fully complete for its complexity.

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% with a single parameter 'limit' described as 'Max entities to return'. The description adds an example usage, which is marginal value beyond the schema. Baseline 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 explicitly states it gets trending entities (people, orgs, topics) with the most mentions in the last 24 hours. While it is clear, it does not distinguish from similarly named sibling tools like 'veroq_social_trending', which may have overlapping functionality.

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 a 'WHEN TO USE' section that tells the agent to use it to discover what's dominating the news cycle and as a good starting point for research. However, it does not explicitly state when not to use it or compare to 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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