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

The annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond annotations by describing the canonical, fixed nature of the list (26 systems) and enumerating the fields returned, making the stable read-only behavior concrete.

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 entire description is one well-structured sentence. It front-loads the action and resource, then gives the return content, then the exact usage trigger. Every clause earns its place with no 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?

For a zero-parameter, read-only, list-returning tool, the description is complete: it states the tool's purpose, the list contents, the count of systems, and the exact user query that should invoke it. The absence of an output schema is compensated by enumerating the returned fields.

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, so there is no parameter meaning for the description to clarify. The baseline for 0-parameter tools is 4, and the description appropriately avoids inventing parameter details.

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 a specific verb ('Return') and a precise resource ('canonical list of 26 ancient divination systems'), and details exactly what the list contains: slug, English + Thai name, region, required inputs. This clearly distinguishes it from siblings like get_system_rules, which focuses on rules rather than an overview list.

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?

It gives an explicit trigger: 'Use first when asked "what systems do you support?"' This tells the agent when to select this tool. It does not explicitly name alternatives or state when not to use it, but the contextual trigger is clear and actionable.

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