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

With no annotations, the description carries the full burden and does substantial work: it discloses grain differences (advertised_asins as current entity-synced state, product_ads per-ad, asins_served_in_window as report view), notes never-served ads, and flags source terminology. It omits response format and rate-limit details, but the key behavioral nuances are surfaced.

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?

Two sentences, zero filler. The primary purpose is front-loaded, followed by a dense GRAIN clarification that earns its place, and the workflow statement closes efficiently. No information is repeated.

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?

Despite having no output schema and several non-obvious semantics, the description covers the critical distinctions that would trip up an agent: what each data grain means, the SP-only limitation, and the intended sequencing after ppc_campaigns. It doesn't describe response shape or error behavior, but the most decision-relevant context is present.

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 only 40% (only profile_id is described in-schema). The description adds meaning for the date range via 'asins_served_in_window ... scoped to the requested range' and for campaign_ids via 'specific SP campaigns', but it does not explain date formats, optionality, or how the parameters map to the listed output categories. It partially compensates for the low schema coverage but leaves gaps.

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 states a specific verb+resource ('Get detailed data for specific SP campaigns') and enumerates the payload types (placements, advertised ASINs, placement modifiers, top keywords/targets). It also distinguishes itself from SB/SD tools and explicitly positions itself relative to ppc_campaigns ('drill in'), making sibling differentiation clear.

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 gives a clear workflow cue ('Use this after ppc_campaigns to drill in') and an explicit exclusion ('SP only — SB/SD campaigns come back under notes with the right dataset to query'). It does not name the specific alternative tools for the SB/SD cases, so it is short of a full when/when-not matrix.

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