add_categories

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

With no annotations provided, the description must fully disclose behavioral traits. It mentions 'atomically' and 'active dataset', but does not state if categories are appended or replaced, if duplicates cause failure, whether the operation is idempotent, or if there are any side effects like metadata synchronization. The agent lacks insight into safety, error handling, or rollback behavior.

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 a single, concise sentence with no wasted words. It includes the key qualifier 'atomically' and the condition 'active dataset', which are both critical for correct usage. Every word is meaningful and 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 there is an output schema (not shown but present), the agent may infer return structure. However, the description lacks completeness for a mutation tool with no annotations. It fails to mention error cases (e.g., invalid dataset_id, duplicate names), behavior on non-active datasets, or which sibling tools to use for alternative operations. For a tool with 2 parameters and a clear domain, it is adequate but has clear 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 100%, so the schema already thoroughly documents parameters including type, constraints, uniqueness, and field handling. The description does not add much beyond the schema, but the schema is already rich. The description's term 'atomically' is the only extra semantic value, earning above baseline.

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 verb 'Add categories' and the resource 'active dataset'. The phrase 'atomically' adds precision ensuring the operation is all-or-nothing. However, among siblings like 'edit_category' and 'delete_category', the purpose is clear but could more explicitly distinguish itself from 'add_bbox_annotations' as adding non-annotation metadata.

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 specifies the tool operates on an 'active dataset', implying only datasets with a certain status qualify. However, it provides no guidance on when to use this versus adding categories individually with another tool, no prerequisites like dataset ownership or existence, and no comparison to sibling tools that manage categories (e.g., 'edit_category', 'list_categories').

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