list_tokens

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

With no annotations, the description carries the full burden. It clearly states that the tool lists tokens and returns specific data, implying a non-mutating read operation. It does not mention pagination or error cases, but for a zero-parameter list operation, the core behavior is well disclosed.

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 a single, front-loaded sentence stating the action and then listing exactly what will be returned. Every word provides useful information, and there is no redundancy or bloat.

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 simplicity (no parameters, no output schema), the description is complete: it names the platform, the scope ('all reflection tokens'), and all relevant return fields. No critical information is missing for an agent to select and invoke this 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?

The tool has zero parameters, and the input schema is empty. The description correctly needs no parameter details, and the baseline of 4 applies for the no-parameter case.

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 uses a specific action ('List all reflection tokens') and a clear resource ('on DumbMoney'), and enumerates the returned fields. This makes the tool's purpose immediately obvious and distinguishes it from sibling tools like get_token, which presumably targets a single token.

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 makes the primary use case clear: obtain an overview of all reflection tokens. It does not explicitly mention alternatives or exclusions, but the 'all' scope and field list leave no ambiguity about when to use this tool versus get_token for specific token details.

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