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veroq_compare

Compare news coverage across multiple sources with bias analysis to understand media perspectives on any topic.

Instructions

Compare how different news sources cover the same topic, with per-source bias analysis and synthesis.

WHEN TO USE: When you need to understand media bias or see how coverage of an event differs across outlets. RETURNS: Topic headline, VEROQ confidence/bias scores, per-source analysis, and overall synthesis. COST: 2 credits. EXAMPLE: { "topic": "Federal Reserve rate decision" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesTopic to compare coverage on
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. It successfully documents the cost (2 credits), return structure (headline, scores, synthesis), and provides an input example. However, it omits details about data freshness, source coverage scope, or whether results are cached vs real-time.

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 formatting with clear headers (WHEN TO USE, RETURNS, COST, EXAMPLE). Every sentence serves a distinct purpose. The information is front-loaded with the core function, followed by usage conditions, costs, and examples.

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 single-parameter analysis tool without a structured output schema, the description adequately covers the tool's purpose, inputs, costs, and return format. Minor gaps remain regarding rate limits or source attribution details, but sufficient for correct invocation.

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?

While the schema has 100% coverage for the single 'topic' parameter, the description adds valuable semantic context through the EXAMPLE block showing 'Federal Reserve rate decision', clarifying the expected topic format and granularity beyond the schema's generic 'Topic to compare coverage on'.

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 opens with a specific action (compare) targeting a specific resource (news sources) with clear scope (per-source bias analysis and synthesis). The mention of 'bias analysis' effectively differentiates it from sibling tools like veroq_ticker_news or veroq_feed that likely provide raw news without comparative analysis.

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

Usage Guidelines5/5

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

Contains an explicit 'WHEN TO USE' section stating 'When you need to understand media bias or see how coverage of an event differs across outlets.' This provides clear triggering conditions and distinguishes it from general news retrieval tools.

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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