track_user_preference

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

With no annotations, the description carries the full burden for behavioral disclosure. It merely says 'track and learn' without stating that this is a write operation, how conflicts are handled, or what happens on retries. The mention of 'learn' hints at persistence but lacks explicit detail.

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, front-loaded sentence with zero wasted words. It is efficient and to the point, though it is under-specified for the tool's complexity.

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 tool has six parameters and no annotations or output schema, yet the description fails to explain return behavior, default values, or how the tracked preferences can be retrieved. Agents are left without a full understanding of the workflow.

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?

The input schema provides rich descriptions for all six parameters (100% coverage), so the description need not explain them. The description adds no extra meaning about parameter interactions, such as how 'category' or 'confidence' affect learning.

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 identifies the tool's action ('track and learn') and resource ('user preferences'), but the meaning of 'learn' is vague and it does not differentiate from siblings like 'get_user_preferences' or 'track_preferences_batch'.

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 no guidance on when to use this tool versus alternatives such as 'get_user_preferences' for retrieval or 'track_preferences_batch' for batch operations. It lacks any contextual prerequisites or exclusion criteria.

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