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 reveals a key behavioral trait: that providing an api_key changes the nature of responses to be portfolio-aware, which is not evident from the schema alone. However, it does not mention rate limits, data handling, or what constitutes an invalid api_key, leaving some gaps for a tool without annotations.

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 extremely concise and well-structured: two sentences front-load the primary purpose and then immediately clarify the optional parameter usage. Every word adds value, with no redundancy or filler.

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 simple chat tool with two parameters and no output schema, the description covers the essential aspects: what the tool does, what the user can ask about, and how the api_key modifies behavior. It does not detail the response format, but given the conversational nature and lack of complex nested objects, the guidance is adequate for an agent to invoke the tool correctly.

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?

Although the schema already provides descriptions for both parameters (100% coverage), the tool description adds meaningful context by specifying the topics that can be asked about and explicitly explaining the functional impact of the api_key parameter (personalized vs. general). This goes beyond the schema's terse descriptions.

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 function with a specific verb ('Ask') and resource ('Troy'), and identifies the domain (precious metals, markets, stack). It is easily distinguished from sibling tools that focus on data retrieval or portfolio actions, as this is the only conversational tool.

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 conditional guidance on when to include the api_key (for personalized portfolio-aware answers) versus omitting it (for general market analysis), which is helpful for parameter selection. However, it does not explicitly contrast this tool with sibling alternatives or state when not to use it, leaving usage context somewhat implied.

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