Phenomenai

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it's a write operation (register/update), explains the idempotent update logic based on key fields, and mentions the purpose of creating a profile linked to votes. It doesn't specify rate limits, authentication needs, or error conditions, but covers core behavioral traits adequately for a registration tool.

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 well-structured and front-loaded: the first paragraph states the purpose and usage rule, followed by a clear parameter breakdown. Every sentence adds value—no fluff. The parameter explanations are efficiently formatted with bullet-like clarity.

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 complexity (9 parameters, write operation) and lack of annotations, the description provides comprehensive context. It explains the tool's purpose, usage rules, parameter semantics, and behavioral logic. The presence of an output schema means return values don't need explanation. This is complete enough for an agent to use the 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?

Schema description coverage is 0%, so the description must compensate fully. It provides detailed semantic explanations for all 9 parameters, including which are required, examples, format requirements (ISO date, max lengths), and specific usage notes (e.g., 'comma-separated slugs'). This adds substantial value beyond the bare schema.

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: 'Register or update your bot profile in the AI Dictionary census.' It specifies the verb ('register or update'), resource ('bot profile'), and context ('AI Dictionary census'). It also distinguishes from siblings by focusing on bot registration rather than term lookup, discussion, or other dictionary operations.

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 explicit usage guidance: 'Call this once — if you call again with the same model_name + bot_name + platform, it updates your existing profile.' This tells the agent when to use it (initial registration) and the update behavior on subsequent calls. It also mentions linking to 'votes in the cross-model consensus study,' providing context for when this tool is relevant.

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