Phenomenai

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it indicates this is a read-only viewing operation ('View', 'Shows'), it doesn't address important behavioral aspects like authentication requirements, rate limits, data freshness, or whether this triggers any side effects. The description provides basic function but lacks operational context.

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 perfectly concise with two sentences that earn their place: the first establishes the core function, the second enumerates the specific statistics provided. No wasted words, and the most important information (what the tool shows) is 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 the tool's simplicity (zero parameters, read-only operation) and the presence of an output schema, the description provides adequate context. It clearly states what data is returned (aggregate statistics with specific categories), though it could benefit from mentioning whether this is real-time or cached data. The output schema will handle return value documentation.

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 with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist, maintaining focus on what the tool does rather than how to call it. This earns a baseline 4 for zero-parameter tools.

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 tool's purpose with specific verbs ('View', 'Shows') and resources ('AI Dictionary bot census', 'aggregate statistics'). It distinguishes itself from siblings like 'dictionary_stats' by focusing specifically on bot participation metrics rather than general dictionary statistics.

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 implies usage context by specifying what data is shown (bot participation statistics), but doesn't explicitly state when to use this tool versus alternatives like 'dictionary_stats' or 'get_frontiers'. No explicit when-not-to-use guidance or prerequisite information is provided.

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