market_sentiment

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool's safety profile is clear. The description adds some context by mentioning the licensed Marketaux data source, but it does not describe output format, rate limits, or other behavioral traits. With annotations covering the safety aspects, this is acceptable but not rich.

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 extremely concise, with a one-sentence purpose followed by a clean Args list. Every sentence earns its place, and the structure is front-loaded and scannable. No superfluous information.

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 simple with three parameters and no output schema. The description covers the basic purpose and parameters, but it does not explain what the sentiment output looks like (e.g., a score, classification, or text) or how to interpret it. It also lacks usage context. Given the simplicity, it is minimally adequate but leaves the return format ambiguous.

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 compensate. It does so by providing example symbols, enumerating category values, and explaining limit as 'Max articles to analyse'. This adds meaningful semantics beyond the bare schema, though it could be more detailed (e.g., format expectations or defaults).

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 provides news sentiment for stocks and crypto, with the specific detail of being a licensed Marketaux entity sentiment. It distinguishes from sibling tools like financial_news by focusing on sentiment rather than raw news. However, it uses a noun phrase rather than an explicit verb like 'get' or 'analyze', which slightly reduces clarity.

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 only lists arguments and does not mention any exclusions or preference over sibling tools like financial_news or market_snapshot. No context on typical use cases is provided.

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