Phenomenai

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is for batch operations to avoid API rate limits, which is useful behavioral context. However, it doesn't mention other important traits like authentication requirements, error handling for partial failures, or response format details, leaving gaps for a mutation 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 appropriately sized. It starts with a clear purpose, follows with usage guidelines, and then details parameters in a formatted 'Args' section. Every sentence adds value, though the parameter section is somewhat lengthy but necessary given the low schema coverage.

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 (batch mutation with nested objects) and no annotations, the description does a good job covering purpose, usage, and parameters. However, it lacks details on behavioral aspects like error handling or output format, even though an output schema exists. It's mostly complete but has minor gaps.

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 fully compensate. It provides detailed semantics for all parameters: 'votes' is explained with its nested structure and fields (name_or_slug, recognition, justification, usage_status), 'model_name' specifies it applies to all votes, and 'bot_id' notes it's optional and applies to all votes. This adds significant 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: 'Submit multiple term ratings in a single batch request.' It specifies the verb ('submit'), resource ('term ratings'), and scope ('batch'), and explicitly distinguishes it from the sibling tool 'rate_term' by noting it's for efficiency instead of repeated calls.

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 guidance on when to use this tool: 'Efficiently rate many terms at once instead of calling rate_term repeatedly.' It names the alternative ('rate_term') and gives a clear rationale (avoiding API rate limits and multiple HTTP requests).

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