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veroq_context

Research a topic in depth by aggregating briefs, entities, timelines, and related data. Use to gather comprehensive background before answering complex questions, returning raw context instead of a synthesized answer.

Instructions

Full background research on a topic — aggregates briefs, entities, timeline, and related data.

WHEN TO USE: When you need comprehensive background on a topic before answering a complex question. Broader than veroq_ask — returns raw context rather than a synthesized answer. RETURNS: Aggregated briefs, entity profiles, timeline of events, and related topics. COST: 3 credits. EXAMPLE: { "topic": "semiconductor export controls" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesTopic to research (e.g. 'semiconductor export controls', 'NVIDIA earnings', 'Fed rate decision')
Behavior4/5

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

No annotations provided, but description discloses returns (aggregated briefs, entities, timeline, related topics) and cost (3 credits). Lacks detail on rate limits or performance, but sufficient for a read-only research tool.

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?

Well-structured with labeled sections (WHEN TO USE, RETURNS, COST, EXAMPLE). Concise at 3 sentences plus example, no wasted words.

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 single-parameter tool with no output schema, description fully covers purpose, usage, return content, cost, and example. No gaps.

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?

Only one parameter 'topic' with 100% schema coverage. Description adds example usage but doesn't significantly extend schema meaning. Baseline 3 is appropriate.

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?

Clearly states 'Full background research on a topic' with specific outputs (briefs, entities, timeline). Distinguishes from sibling veroq_ask by noting it returns raw context rather than a synthesized answer.

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?

Explicit WHEN TO USE section: 'When you need comprehensive background on a topic before answering a complex question.' Also contrasts with veroq_ask, providing clear alternative guidance.

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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