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

With no annotations provided, the description carries the behavioral disclosure burden. It explains what the tool returns per analyst (overall stance, mentioned tickers, recent points) and adds an important presentation constraint: summarize rather than reproduce tweets verbatim, and attribute each view. This is meaningful behavioral context beyond the input schema.

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 front-loaded with the core purpose, then provides a compact example, return summary, and presentation rule. Every sentence adds useful information, and there is no filler or repetition of the parameter schema.

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?

For a reasonably simple fetch tool with an output schema available, the description covers the essential input semantics, return content, and how to present results. It misses only minor items like the limit_per_analyst parameter and explicit routing against sibling tools, so it is almost complete but not exhaustive.

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 explains 'handles' with a concrete example and 'ticker' as optional, but it does not mention 'limit_per_analyst' at all. The missing parameter is partially self-explanatory from its name, but the description does not fully bridge the documentation gap.

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 opens with a specific, actionable statement: 'Fetch the recent views of specific X analysts/KOLs by handle.' This clearly names the resource (analyst views), the action (fetch), and the key input (handle), and it distinguishes the tool from siblings like analyst_recent_calls by focusing on 'views' rather than calls.

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 gives clear context for when to use the tool: when the user names specific analysts/KOLs, with an optional ticker focus. It does not explicitly contrast with alternatives or state when not to use it, but the usage context is strong enough that an agent can infer the right selection.

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