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search_symbol

Find the ticker symbol for any company or asset by name. Converts names like 'Nvidia' into tickers for use in market data queries.

Instructions

Find the ticker for a company or asset by name.

Args: query: Company or asset name, e.g. "bank central asia" or "nvidia". limit: Maximum matches to return.

Use this first whenever the user names a company rather than a ticker.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses that the search may return multiple matches through the 'limit' parameter, but it does not describe the output structure or error behavior. However, an output schema exists, which reduces the need for return-value detail. Slight gap remains regarding result format and potential edge cases.

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 compact and well-organized: a one-sentence purpose, a brief Args section, and a final usage directive. Every sentence adds value, with no redundancy or filler.

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 2-parameter search tool with an output schema, the description covers all essential aspects: purpose, parameter meaning, and when to use it. The context signals show no nested objects and an output schema, so return-value details are already available. The description is sufficient for an agent to select and call the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description fully explains both parameters: 'query' with examples ('bank central asia', 'nvidia') and 'limit' as 'Maximum matches to return.' This adds clear meaning beyond the raw schema and provides practical usage context.

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 the tool's function: 'Find the ticker for a company or asset by name.' It uses a specific verb ('Find') and resource ('ticker'), and differentiates from siblings by noting it should be used first when a user provides a company name rather than a ticker.

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 guidance is provided: 'Use this first whenever the user names a company rather than a ticker.' This tells the agent when to invoke this tool and implicitly when to skip it, contrasting with sibling tools that likely require a ticker.

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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