update_attention

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

Annotations are absent, so the description must fully disclose behavioral traits. It mentions 'update' implying mutation but does not specify if the operation is destructive, what state changes occur, or any side effects beyond the vague 'attention system'.

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?

Single well-structured sentence, no redundancy, and front-loaded with key action and purpose.

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?

Without output schema and with no behavioral details, the description is insufficient for an agent to understand the full impact or expected output of the update operation. It omits what the 'attention system' is and what updates entail.

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?

Input schema has 100% description coverage, so baseline is 3. The description adds value by enumerating activity types and linking them to the purpose, but does not explain parameter interactions or conditions (e.g., when query_text is required).

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 action ('Update attention system from user activity'), specifies the activity types (file access, edits, errors, successes), and communicates the purpose ('dynamic attention learning'). This distinguishes it from sibling tools like 'allocate_attention' or 'get_attention_stats'.

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?

No guidance is provided on when to use this tool versus alternatives or when not to use it. The description gives no context for tool selection or prerequisites.

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