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

The description adds substantial behavioral detail beyond the annotations: it lists the exact returned fields, states that no merchant links are returned, explains what canonical_page and site_entry_page contain, and warns that links are user_navigation handoffs not intended for prefetching or automatic clicking. It also confirms the read-only nature, consistent with readOnlyHint=true. This is exemplary transparency for a list endpoint.

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 long but every sentence carries useful information: purpose, ordering, output fields, filters, exclusions, page semantics, and link-handling warnings. It is front-loaded with the core purpose and then details. It could be slightly tightened, but the density is justified because there is no output schema to document the return shape.

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 read-only list tool with no output schema and seven parameters, the description is remarkably complete. It names all relevant output fields, explains the default state filter, clarifies the relationship to get_current_offers, describes the canonical and site entry pages, and warns about link handling. An agent has enough context to invoke the tool correctly and interpret the response.

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 86%, so the schema already documents most parameters. The description mentions the filters ('brand slug, category slug, kind, source, state (running by default), limit, cursor') but adds little beyond what the schema states; for example, 'state (running by default)' repeats the schema default. It does not explain cursor pagination or the slug normalization beyond the schema. This meets the baseline but does not exceed it.

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 opens with a specific verb and resource: 'Lists the sales and campaigns recorded by a Japanese music-production buying guide (region JP), running ones first'. It clearly identifies the tool's scope and differentiates it from get_current_offers by stating that per-product offers are handled there. This is far beyond a tautology and gives an agent a precise mental model.

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 gives clear context for when to call this tool: to list campaigns/deals with filters, running campaigns by default. It explicitly routes per-product offer lookups to get_current_offers ('offers of one product are returned by get_current_offers'). It does not explicitly contrast with search_products, compare_products, or resolve_purchase_request, but the use case is clear enough that an agent can select it appropriately.

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