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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds behavioral details: even split by default, weights for custom mix, total overriding target, and a prerequisite ('needs male_female targeting'). This goes beyond the annotations, though it doesn't state whether existing limits are overwritten or additive. It is consistent with annotations.

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 compact and front-loaded with the main action, followed by examples and default behavior. Every clause adds value: scope examples, default even split, weights, and total. No filler or redundancy. It is well-structured for quick comprehension.

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 tool with 5 parameters, a nested object, and no output schema, the description covers the core aspects: purpose, scope options, default behavior, and parameter effects. It notes a prerequisite for gender targeting. It could be more explicit about the effect on existing quota limits or required setup, but it is generally complete given the annotations and schema richness.

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 coverage is 100%, providing baseline 3. The description adds meaning beyond the schema by explaining how scope maps to cells (e.g., 'gender' = 50/50 male/female), that weights are for a custom mix, and that total overrides the target. These clarifications help an agent understand parameter usage beyond the basic descriptions.

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 action ('Spread the completes target across cells') and specifies the resource (quota cells). It distinguishes itself from siblings like create_quota or update_quota by focusing on splitting a target, not creating or editing quotas directly. Examples (gender, age, quota_ids) further clarify the purpose.

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?

It provides clear context for when to use the tool by explaining the scope options and giving examples. However, it does not explicitly mention when not to use it or name alternatives, such as set_target_completes or update_quota. The guidance is sufficient for most cases but lacks explicit exclusions.

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