list_augments

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

No annotations are present, so the description must fully disclose behavioral traits. The description only states the basic function and output format. It does not mention authentication requirements, rate limits, pagination, sorting order, or what happens with invalid parameters. This lack of behavioral context is a significant gap for a tool that likely performs a read operation.

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 relatively concise, with the main purpose in the first sentence. The parameter details are presented in a bullet-like format that is easy to scan. However, it could be more structured (e.g., using a table or explicit argument list) and the first line could be slightly more formal. Overall, it is efficient and front-loaded.

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 that the tool has an output schema, the description does not need to detail return values. It explains the output (name + effect summary) and the filtering parameters. However, it does not mention whether the list is sorted, if there are any limits on results, or the default behavior when 'tier' is 'all'. This leaves some operational gaps for an agent to infer.

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 has 0% coverage with no parameter descriptions. The description compensates by explaining 'tier' with a clear list of values and 'locale' with two options. It also notes that Chinese aliases are accepted. This adds substantial meaning beyond the schema's defaults, making it easy for an agent to construct valid arguments.

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 verb ('list') and resource ('arena hex augmentation list'), and specifies the output (name + effect summary). The purpose is specific and aligns with the tool name. However, it does not distinguish this tool from siblings like 'get_augment' or 'mayhem_balance', which could cause ambiguity for an AI agent.

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 parameter details including allowed values for 'tier' and 'locale', and mentions Chinese aliases. It implies usage for listing augments by rarity. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'get_augment' for a single augment) or give any exclusion criteria, leaving some navigational ambiguity.

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