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

Annotations already declare read-only, idempotent, non-destructive, and open-world behavior. The description adds valuable content-level transparency by explaining that real-money runs include BscScan links while paper runs are marked as paper, and that every trade since launch is included.

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 definition is a single, front-loaded sentence that begins with the core resource and then lists the returned contents. Every clause adds useful information without redundancy.

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?

There is no output schema, so the description carries the burden of explaining return contents, and it does so well by naming the value history, rules, engine decision, and trade history. It stops short of describing response structure or pagination, but is otherwise complete for an agent selecting and invoking the 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?

The schema documents only that slug is a required string, with 0% schema description coverage. The description compensates by explaining that slug comes from list_live_runs, which is the key semantic needed to supply the parameter correctly.

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 identifies the resource as one public live run and enumerates the specific data returned: value over time, rules, last engine decision, and all trades. It also distinguishes this from the sibling list_live_runs by stating that the slug comes from that 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 establishes that you need a slug obtained from list_live_runs, giving clear usage context. It does not explicitly state when not to use this tool or name other alternatives, but the prerequisite routing is sufficient for an agent to select it correctly.

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