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veroq_analysts

Retrieve consensus Wall Street analyst ratings, mean/high/low price targets, and individual firm ratings with target prices and dates for any stock ticker.

Instructions

Get Wall Street analyst ratings and price targets for a stock.

WHEN TO USE: To see consensus analyst opinion and price target range for a stock. RETURNS: Consensus rating, mean/high/low price targets, analyst count, and individual ratings with firm, target, and date. COST: 2 credits. EXAMPLE: { "ticker": "NVDA" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesTicker symbol (e.g. AAPL, NVDA, TSLA)
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It details return data: consensus rating, mean/high/low targets, analyst count, and individual ratings. It also mentions the cost (2 credits). This adequately discloses behavior for a read-only query.

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 concise and well-structured, using labeled sections (WHEN TO USE, RETURNS, COST, EXAMPLE). Every sentence is necessary and information-dense, with no wasted words.

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 simple one-parameter tool with no output schema, the description covers purpose, usage, return structure, cost, and an example. It could mention potential restrictions like ticker validity, but overall it is sufficiently complete.

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?

Schema coverage is 100% with a single 'ticker' parameter having a description. The description adds value through an example ('{ "ticker": "NVDA" }') and context about usage, going beyond the schema's basic definition.

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 clearly states 'Get Wall Street analyst ratings and price targets for a stock,' providing a specific verb and resource. It distinguishes itself from siblings like 'veroq_earnings' and 'veroq_ticker_analysis' by focusing on analyst ratings.

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?

The description explicitly says 'WHEN TO USE: To see consensus analyst opinion and price target range for a stock,' offering clear context. It does not explicitly mention when not to use or alternatives, but the given guidance is sufficient.

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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