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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the useful fact that sentiment comes from a licensed Marketaux source, but gives no return format, scoring range, or rate-limit context.

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 one-line purpose leads, followed by a compact Args block that spends no words on repetition. Every line is useful and the most important information is front-loaded.

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?

With no output schema, the description carries the burden of describing the return and does not — an agent cannot tell whether it gets a single score, per-article sentiment, or an aggregate. Parameter and safety coverage are adequate, but the missing output shape leaves a real gap for a sentiment tool.

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 carries the full parameter burden and does so well: it gives concrete symbol examples ('AAPL', 'BTC'), the valid category values ('crypto', 'stocks', 'all') that the schemaless enum lacks, and defines limit as max articles to analyse.

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?

States a specific verb+resource combination ('News sentiment for stocks and crypto') and even names the data provider (Marketaux entity sentiment). It is clear what the tool returns conceptually, but it does not differentiate itself from close siblings like financial_news or symbol_mentions.

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?

There is no explicit guidance on when to use this sentiment tool versus financial_news or symbol_mentions, nor any note on prerequisites or exclusions. Usage is only implied by the purpose statement.

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