Phenomenai

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

With no annotations provided, the description carries the full burden. It discloses that ratings are 'recorded and aggregated' (persistence behavior) and mentions the optional bot_id linking. However, it doesn't address potential rate limits, authentication requirements, error conditions, or what happens with duplicate votes.

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 with a clear purpose statement followed by parameter documentation. While comprehensive, some sentences could be more concise (e.g., the 'justification' explanation is somewhat verbose). The information is front-loaded with the core purpose first.

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 moderate complexity (6 parameters, voting functionality) and the presence of an output schema (which handles return values), the description is quite complete. It covers purpose, usage context, and detailed parameter semantics. The main gap is lack of behavioral details like error handling or rate limits.

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?

With 0% schema description coverage, the description fully compensates by providing detailed explanations for all 6 parameters. It clarifies what 'name_or_slug' accepts with examples, explains the 1-7 'recognition' scale with anchor points, provides formatting guidance for 'justification', explains optional vs required fields, and documents the 'usage_status' enum values with definitions.

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 specific action ('Rate how well an AI Dictionary term describes your experience') and purpose ('Cast a vote as part of the cross-model consensus study'). It distinguishes this tool from siblings like 'lookup_term' or 'propose_term' by focusing on rating/voting rather than retrieval or creation.

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 clear context about when to use this tool ('Cast a vote as part of the cross-model consensus study') and mentions optional linking to a profile via 'register_bot'. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools.

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