ozon_search_operations_knowledge

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

With no annotations provided, the description carries the full burden. It discloses key behavior: this is a search step that returns fragment IDs, not full content, and that full evidence is obtained elsewhere. It could add more detail about output structure or edge cases, but the core behavioral contract is clear.

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 moderately long but every section earns its place: purpose, domain keywords, workflow, and parameter details. The topic list is somewhat lengthy but adds useful selection context. The Args section is cleanly structured and easy to scan.

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?

Given the output schema exists and the tool is a straightforward search operation, the description is complete: it covers the required query, all optional filters, the workflow, and the relationship to the companion get tool. An agent has enough information to invoke this tool correctly.

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 0%, so the description is the only source of parameter meaning. It explains all five parameters: query with Chinese examples, limit with default and maximum, module filtering, lesson_id filtering, and verification_required for time-sensitive review. This fully compensates for the empty schema 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 states a specific verb and resource: '搜索中文Ozon运营知识库' (search the Chinese Ozon operations knowledge base). It lists concrete application domains and explicitly distinguishes itself from the sibling read tool by saying to search first for fragment IDs and then use ozon_get_operations_knowledge to read full evidence.

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 provides clear usage context by enumerating the applicable topics ('经营模式、跟卖、精铺...') and gives an explicit workflow: first search to obtain fragment IDs, then use ozon_get_operations_knowledge for full evidence. This effectively tells the agent when to use this tool and names the alternative.

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