create_term

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

With no annotations provided, the description carries the full behavioral burden. It discloses authentication via API token and scopes the operation with 'Only the created term's AI metadata is affected,' which is valuable context. It also flags the mandatory AI-tracking fields. It does not describe broader side effects, but the mutating nature is clear from the tool name.

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 concise and front-loaded: it states the creation purpose first, then explains term relationships, then provides the critical AI-metadata instruction. Each sentence earns its place and nothing is redundant.

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 rich input schema and the absence of an output schema, this description is nearly complete for invocation. It covers authentication, creation scoping, and AI-metadata requirements. It could be slightly more complete by mentioning likely response behavior, but that is not required for correct calling.

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 100%, so the baseline is 3. The description adds real value by requiring aiMetadata with ai_generated=true, ai_model, and ai_generation_date for AI-generated terms—ai_generation_date is not listed as required by the schema's conditional logic. It also clarifies that only the created term's AI metadata is affected, which helps an agent reason about parameter scope.

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 a specific action and resource: 'Create a new individual term' and emphasizes that terms can exist independently or be linked to term groups. This distinguishes create_term from the list, get, and update siblings. The purpose is unambiguous even without opening the schema.

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 gives some context about term relationships and an important AI-metadata rule, but it never says when to choose this tool over alternatives like update_term or create. An agent must infer the usage boundary from the tool name alone.

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