get_forex_sentiment

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 mentions the return structure and price ('$0.40'), which adds some context. However, it lacks critical details such as rate limits, authentication requirements, error handling, or whether the analysis is real-time or cached. For a paid tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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 well-structured and concise. It starts with a clear purpose statement, lists parameters with brief explanations, specifies the return format, and ends with pricing information. Every sentence adds value without redundancy, and the information is front-loaded for quick comprehension.

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?

Given the complexity (AI-powered analysis with multiple factors), no annotations, and an output schema (implied by 'Returns'), the description is fairly complete. It covers parameters thoroughly and outlines the return structure. However, it lacks details on behavioral aspects like cost implications or usage limits, which are important for a paid tool, preventing a perfect score.

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?

Schema description coverage is 0%, so the description must fully compensate. It does so effectively: it explains all four parameters with clear semantics—'pair' as the currency pair with examples, and the three boolean flags specifying what to include in the analysis. This adds substantial meaning beyond the bare schema, making the parameters well-understood.

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 purpose: 'Get AI-powered forex currency pair sentiment analysis.' It specifies the verb ('Get') and resource ('forex currency pair sentiment analysis'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_sentiment_analysis' or 'get_stock_sentiment,' which is why it doesn't achieve a perfect score.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_sentiment_analysis' or 'get_stock_sentiment,' nor does it specify prerequisites, exclusions, or contextual triggers for its use. The only implicit guidance is the parameter descriptions, which are insufficient for usage decisions.

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