Finance Tools MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's function and parameter usage but lacks critical behavioral details such as rate limits, authentication requirements, data freshness, pagination, or error handling. For a tool fetching real-time social media data, these omissions are significant gaps that could impact agent decision-making.

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 appropriately sized and front-loaded, with the core purpose stated first. Each sentence adds value: the first defines the tool, the second gives usage context, and the remaining sentences detail parameter behavior with examples. There's no redundant information, though the structure could be slightly improved by separating the examples into a bullet list for readability.

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's moderate complexity (fetching social media data), no annotations, and no output schema, the description is partially complete. It covers the purpose and parameter usage well but lacks details on output format, data recency, limitations, or error cases. This leaves gaps that could hinder an agent's ability to use the tool effectively in varied contexts.

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 schema description coverage is 0%, so the description must compensate. It effectively explains the 'keywords' parameter: it's optional, used to match specific topics via 'OR' operator, and provides concrete examples like ['tsla', 'tesla']. This adds meaningful semantics beyond the bare schema, clarifying how the parameter influences the tool's behavior and output.

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's purpose: 'Get most discussed stocks and investments opinions from reddit.' It specifies the verb ('Get'), resource ('stocks and investments opinions'), and source ('from reddit'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'cnbc_news_feed' or 'get_ticker_news_tool', which might also provide financial content from different sources.

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 provides clear context on when to use the tool: 'Useful to know what investors are talking about.' It explains the optional parameter behavior: 'No keywords will return the most discussed stocks and investments.' However, it doesn't explicitly state when NOT to use this tool or mention alternatives among the sibling tools, such as using 'cnbc_news_feed' for professional news instead of social media opinions.

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