get_contract_data

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

With no annotations provided, the description carries full transparency burden. It discloses that it queries an API, automatically handles some parameters (numOfRows, pageNo, type, serviceKey), supports pagination via fetch_all, and imposes a 1-month date range limit. It does not describe mutability or auth needs, but the overall behavior is well-explained.

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 well-structured: it starts with overall purpose, then instructions, a complete list of operations (necessary for this complex tool), common parameters, and warnings. While lengthy, it avoids redundancy and every sentence provides useful information. The list of operations could be more concise, but it helps the agent understand available sub-functions.

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 tool's complexity (21 operations, multiple optional parameters, no output schema, no annotations), the description is fairly complete. It explains how to use the tool, pagination behavior, date constraints, and directs users to get_g2b_operation_info for detailed parameter/response fields. Rate limits or exact return structure could be added, but overall it provides sufficient context for an AI agent.

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?

Although the schema already describes all parameters (100% coverage), the description adds significant value: it lists common query conditions (inqryDiv, inqryBgnDt, etc.), explains that numOfRows/type/serviceKey are auto-handled, describes the meaning of fetch_all, and provides context for each of the 21 operations. This goes well beyond the 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 clearly states it is a tool for querying the Korea Procurement Service OpenAPI for contract data, and lists 21 specific sub-operations. The verb 'get' and resource 'contract data' are explicit, distinguishing it from sibling tools that handle different data types like bid or industry data.

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 detailed usage instructions: specify an operation, pass parameters as a dict, use get_g2b_operation_info for exact fields, and handle pagination. It warns about date range limits (1 month) and explains automatic param handling. However, it does not explicitly contrast with sibling tools or state when not to use this tool.

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