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

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real behavioral context not in the annotations: pricing is set by the Kognai CFO and the call itself is free, which tells the agent there is no charge for invoking it. It does not describe the response shape or payment mechanics in any depth.

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?

One dense sentence with no filler, and the subject (what the service does/never does) is front-loaded. It is terse but not padded, which suits a small informational tool.

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 zero-parameter, read-only info tool this is nearly adequate, but it omits what the response actually contains (structured text? a URL? a price table?) and gives no indication of payment flow details, leaving the agent to discover the return format on the first call.

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 tool takes zero parameters and the schema is fully described, so there is nothing for the description to disambiguate. Baseline for a no-parameter tool applies.

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 names the resource ('Golden Kog') and enumerates the content the tool returns: what it does/never does, prices, and how to pay. That is clear and distinct from the token-analysis siblings (analyze_token, resolve_ticker, monitor_token). It stops short of a crisp verb like 'retrieve service info', but an agent can still tell what the call yields.

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?

Usage is only implied: an agent infers it should call this to learn about the service before paying. There is no explicit when/when-not and no mention of the sibling tools, though the informational nature makes the boundary fairly obvious. 'Free' hints at a no-cost precondition but isn't framed as guidance.

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