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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds context about the analyzer-inspection use case and the slug/scope scoping, but it doesn't disclose additional behavioral details such as pagination behavior, error cases, or return shape beyond the basic listing operation.

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 two short sentences with no filler. The core operation is front-loaded, and the added use-case sentence earns its place by helping the agent understand intent.

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, read-only list operation with well-documented parameters and helpful safety annotations, the description plus schema is largely sufficient. It could be more complete with a note about the response shape or what happens when a slug doesn't exist, but nothing critical is missing for a correct call.

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 100%, so the input schema already fully documents slug, scope, and limit. The description mentions 'by slug and scope' but adds no parameter-level meaning beyond what the schema provides, warranting the baseline score of 3.

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 uses a specific verb ('List') and a clear resource ('(key, value) entries of a given dataset'), scoped by slug and scope. This distinguishes it from sibling tools like list_datasets and add_dataset_entry/remove_dataset_entry without needing to open their schemas.

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 phrase 'Useful for inspecting what an analyzer will match against' gives a concrete use case and clear context for when to call this tool. It does not explicitly name alternatives or exclusions, so it stops short of a 5.

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