get_startup_checklist

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool outputs (checklists, permits, costs, sequences) but lacks critical behavioral details such as whether it's a read-only operation, if it requires authentication, rate limits, or how data is sourced. For a tool with no annotation coverage, this is a significant gap in transparency.

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 concise and front-loaded, consisting of two efficient sentences that directly state the tool's offerings. There's no unnecessary information, and each sentence contributes to understanding the tool's purpose. However, it could be slightly more structured by explicitly separating outputs (e.g., checklists vs. costs).

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 moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers what the tool provides but lacks details on behavioral aspects, output format, or error handling. Without annotations or an output schema, the description should do more to compensate, but it meets a basic threshold for a read-oriented tool.

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?

The input schema has 100% description coverage, clearly documenting both parameters ('business_type' and 'region') with examples. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how 'region' affects results or providing more context on 'business_type' options. Baseline score of 3 is appropriate since the schema does the heavy lifting.

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 the tool's purpose: providing industry-specific startup checklists, required permits, estimated costs, and preparation sequences. It uses specific verbs ('안내합니다', '제공합니다') and identifies the resource ('창업 체크리스트와 필요 인허가'). However, it doesn't explicitly differentiate from sibling tools like 'recommend_policy_funds' which might also provide financial guidance, leaving room for ambiguity.

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 offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare with sibling tools such as 'analyze_commercial_area' or 'find_competitors', which might be relevant for startup planning. Usage is implied through the description's content but not explicitly stated.

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