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search_news

Find relevant news articles by entering a search query and specifying the number of results to retrieve.

Instructions

Search for news articles using a query string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
news_countNoThe number of news articles
queryYesThe search query
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Search for news articles') but fails to describe key behaviors: it doesn't specify the source or scope of news, potential rate limits, authentication needs, error handling, or the format of returned results. For a search tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly. This exemplifies good conciseness and structure for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity as a search function with no annotations and no output schema, the description is incomplete. It doesn't explain what the search covers, how results are returned, or any limitations. For a tool that likely returns multiple articles, more context on result format, pagination, or sorting would be helpful to ensure proper usage by an agent.

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 description coverage is 100%, with both parameters ('query' and 'news_count') clearly documented in the schema. The description mentions 'using a query string', which aligns with the 'query' parameter but adds no additional semantic context beyond what the schema provides. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description offers minimal extra value.

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 clearly states the verb ('Search for') and resource ('news articles') with the mechanism ('using a query string'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'get_ticker_news' or 'search_quote', which might also retrieve news-related information, leaving some ambiguity about when to choose this specific tool.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for usage, or comparisons to sibling tools such as 'get_ticker_news' or 'search_quote', which could be relevant for news retrieval. This lack of differentiation leaves the agent without clear direction on tool selection.

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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