sentiment_analyst

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 only says 'Get', implying a read operation, but it doesn't specify what is returned (e.g., scores, labels), whether there are any rate limits, or auth requirements. For a simple read tool, this is minimal but not misleading.

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 a single, concise sentence with no fluff. It is front-loaded with the core action and resource. While it lacks depth, it doesn't waste words, so it scores well on conciseness and structure.

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 abundance of sibling sentiment tools, the description is too sparse to fully disambiguate usage. It doesn't explain what 'analyst/AI sentiment' means concretely, what data is returned, or how it relates to possibly broader sentiment_all. For a 1-parameter tool it's minimal, but it leaves room for interpretation.

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 coverage is 100% for the only parameter 'ticker', which is described as 'Stock ticker'. The description adds no new meaning beyond that, just rephrases it as 'for a ticker'. With full schema coverage, a baseline of 3 is appropriate.

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 uses a specific verb ('Get'), a clear resource ('analyst/AI sentiment'), and a target ('for a ticker'). It clearly distinguishes this from siblings like sentiment_social and sentiment_news by narrowing to analyst/AI sentiment, so an agent can immediately tell it apart.

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?

No guidance is given on when to use this tool versus alternatives such as sentiment_all, sentiment_social, or sentiment_news. The description states what it does but provides no context on selection. With many sentiment-related siblings, this is a significant gap.

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