get_recommendations

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

No annotations provided, so description carries full burden. Mentions source (Yahoo Finance) but lacks disclosure on data freshness, rate limits, error handling, or safe mutation behavior (likely read-only but not stated).

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?

Description is clear and includes an 'Args' section for structure. It is front-loaded with purpose, but could be trimmed by removing redundant phrasing (e.g., 'from yahoo finance' in both sentences).

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 5 parameters, no output schema, and no annotations, the description should be comprehensive. Missing documentation for 2 parameters and does not explain return format or behavior. Incomplete for a data lookup 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 coverage is 0%, so description must add meaning. It explains 'ticker', 'recommendation_type', and 'months_back', but 'page' and 'export_path' are completely undocumented. Partial value but significant 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?

Clearly states it gets recommendations/upgrades_downgrades for a ticker from Yahoo Finance. However, it does not differentiate from sibling tools like 'get_stock_actions' which might also provide similar data.

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?

Provides some guidance on the 'months_back' parameter and default, but no explicit when-to-use or when-not-to-use compared to other tools. Usage context is implied but not explicitly stated.

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