get_us_analyst

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

No annotations are provided, so the description carries full burden. It explains that the tool returns mean/high/low price targets, buy/hold/sell distribution, and recent upgrades/downgrades. This gives the agent clear behavioral expectations 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 somewhat long with mixed languages and includes an 'Args' section. It is front-loaded with the purpose, but could be more concise by removing redundancy (e.g., example queries could be shorter).

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 tool has one parameter and an output schema (not shown but exists), the description covers the key return fields. It is sufficiently complete for a simple retrieval tool, though it could mention what happens if the ticker is invalid.

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?

The single parameter 'ticker' has 0% schema description coverage. The description adds meaning by providing an example ('NVDA') and specifying it is a US ticker. While not exhaustive, this compensates for the schema 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 clearly states the tool returns US analyst ratings, price targets, and upgrades/downgrades. It provides example queries in both Korean and English, making the purpose unmistakable. It also distinguishes itself from sibling tools like get_consensus by specifying it covers price targets and rating distributions.

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 includes example queries that indicate when to use the tool (e.g., for analyst rating questions). It does not explicitly mention when not to use it or compare to alternatives, but the examples provide good contextual guidance.

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