update_feature

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 two meaningful side effects: the model is rebuilt after modification, and partial changes may persist if the operation fails. This is useful mutation transparency.

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?

Two tight sentences deliver the core action, the scope, and the key failure caveat with no filler. The information is front-loaded and every clause earns its place.

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?

The schema is complex with nested FeatureSettings and DefinitionCall structures, but the description provides no orientation for how to construct the settings payload or identify the target feature. There is also no output schema or explanation of what a successful update returns, leaving significant gaps for correct invocation.

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%, and the description does not compensate. It never explains what document_id or entity_id refer to, nor how the settings object maps to the feature definition. The term 'feature definition' hints at the settings parameter but leaves the required identifiers ambiguous.

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 states a specific verb ('Modify'), a specific resource ('existing native feature definition'), and the consequence ('rebuild the model'). This clearly distinguishes the tool from siblings like create_feature and delete_feature by emphasizing 'existing'.

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 word 'existing' implies this tool is for updating already-created features, not for creating new ones, but it never explicitly names alternatives or states when-not-to-use. The guidance is implied rather than explicit.

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