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

Annotations already declare a non-read-only, idempotent, non-destructive mutation, so the bar is lower; the description adds useful context beyond them: that review and AI moderation are distinct downstream steps (this tool only generates) and that a data_api/api_calls tariff applies, which is real cost/billing disclosure. It doesn't cover output format, but that is partly handled by the receipt semantics in the schema.

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?

Four short sentences with the core action front-loaded and the provenance, moderation-separation, and cost notes following efficiently. No filler, though the phrasing is slightly telegraphic rather than polished.

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 mutating, idempotent, schema-fully-documented tool with no output schema, the definition covers the essential gaps an agent needs: prerequisite experiment sourcing, the fact that moderation is downstream, and the applicable tariff. It could say more about where the generated creative lands, but nothing critical is missing.

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%, including enum and format detail for stance, aspectRatio, and idempotency_key, so the baseline is 3. The description adds only marginal value, clarifying that the advertiser/ad provenance for experiment_id comes from the experiment rather than from caller input.

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?

States a specific verb and resource ('Generate a native brand creative') and adds scope ('for explicit review and moderation'), and the provenance line clarifies that the ad and advertiser derive from the referenced experiment. It does not explicitly differentiate from creative-adjacent siblings like recommend_creative or register_creative_variants, so it stops short of a 5.

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 implies a prerequisite (the experiment supplies the native ad and advertiser, and experiment_id is required), but never states when to choose this over recommend_creative or register_creative_variants. The note that review and AI moderation are separate is process context rather than usage selection guidance, leaving usage implied.

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