opinet-mcp

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

No annotations are provided, so the description carries the full disclosure burden. While it identifies the data source (Opinet), it fails to describe the return structure (e.g., what 'products' are included, format of price data), caching behavior, or whether the data is real-time versus delayed.

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?

Single efficient sentence with zero redundancy. Key scoping terms (전국, 현재, 제품별) are front-loaded and essential.

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 zero-parameter read tool, the description adequately identifies the data retrieved (national current average by product). However, with no output schema provided, the description should ideally hint at the return structure (e.g., list of fuel types with prices) to be complete; this gap leaves it at minimum viable adequacy.

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?

Input schema has zero parameters. Per rubric, 0 params = baseline 4. No parameters require semantic explanation.

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?

States specific action (조회합니다/retrieves), resource (전국 주유소 평균가격/national gas station average prices), and scope (현재 제품별/current, by product). Includes '전국' (nationwide) which implicitly distinguishes it from the sibling 'get_sido_average_price' (regional), but does not explicitly name siblings or contrast scopes.

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?

Provides no guidance on when to select this tool versus siblings like 'get_sido_average_price' (for regional data) or 'get_recent_7days_price' (for trends). The user is not told what granularity or time period this covers relative to alternatives.

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