eval_drift

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

Annotations already declare readOnlyHint=true, so the read-only nature is transparent. The description adds that it returns a JSON string with drift metrics, but does not elaborate on other behavioral traits such as authentication needs or performance impact.

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 concise with three short paragraphs, front-loading the purpose. Every sentence adds value: purpose, explanation, args, returns. No unnecessary words.

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?

For a simple tool with one parameter and an output schema, the description covers purpose, usage, parameter, and return. It could briefly mention that it's read-only, but annotations already cover that, so completeness is high.

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%, so the description must compensate. It explicitly documents the 'days' parameter with meaning ('Number of days to look back'), default value, and identifies the return format, fully addressing the parameter semantics.

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 'Detect memory drift over a time period' and explains it shows counts of created, deleted, and updated memories. This purpose distinguishes it from sibling tools like eval_history or eval_run.

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 says 'Useful for monitoring memory churn,' providing a clear use case. However, it does not explicitly mention when not to use this tool or suggest alternatives among sibling eval tools, so it lacks exclusions.

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