analyze_news_impact

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It adds useful context: the cost per request ($0.001) and that it is AI-driven analysis. However, it does not disclose whether articleId or articleUrl is required, how targetCoins affects the analysis, or what the response format looks like. Some transparency is provided, but significant gaps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences that are front-loaded with the core purpose, immediately followed by cost and methodology. Every piece of text earns its place with no padding or repetition, making it highly efficient and scannable.

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

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

The tool is low-complexity and the input schema is well-documented, but the absence of an output schema means the description should ideally clarify the return format or the required input combination. It does neither. However, the basic purpose and cost are clear, making it minimally viable for an agent to use effectively.

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

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

The input schema provides full descriptions for all three parameters (articleId, articleUrl, targetCoins), giving 100% schema coverage. The description adds no additional parameter-level meaning, so the baseline score of 3 applies. It neither compensates for gaps nor adds redundant details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Analyze potential market impact of a news article' and specifies the domain ('how news might affect crypto prices'). This verb+resource+scope formulation distinguishes it from news-fetching or summarization sibling tools like 'get_defi_news' and 'summarize_article'.

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

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

The description implies the usage context: when you have a news article and want to assess its potential effect on crypto markets. It does not explicitly name alternatives or exclusions, but the purpose is distinct enough to guide selection. A clear context is present without explicit when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.