get_prompt_quality_trend

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

No annotations provided, so description must disclose behavior. It describes a read operation, but does not explicitly confirm it is side-effect-free. It mentions triggering goal-setting, which could be misinterpreted as a side effect of the tool itself. Score 3.

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 three sentences with an Args section, no redundant words, front-loaded with the emoji, and structured efficiently. Score 5.

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 simple tool with one parameter and an output schema existing, the description covers the purpose and usage context. It mentions integration with the optimization loop, but could be slightly more explicit about when to call it. Score 4.

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 description adds semantic value to the 'limit' parameter by explaining it is the number of recent prompts, which the schema lacks. The default is given. This is helpful for an agent, so 4.

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 views prompt quality scores over time, with a specific verb 'View' and resource 'prompt quality trend'. It mentions use by optimization loop, but does not explicitly differentiate from sibling tools like get_quality_trend or analyze, so a 4.

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?

Description implies usage for trend analysis and when quality drops, but does not provide explicit when-not-to-use or alternative tools. So 3.

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