mcp-narajangteo

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

Since no annotations provided, description carries full burden; it successfully discloses return type (formatted string), scope limitation (service-type/용역 projects only), and dual result types (bid notices + preliminary specifications).

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?

Uses efficient docstring structure (Args/Returns), front-loaded with clear purpose statement, every sentence adds value including Korean translations and specific project examples, appropriate length for complexity.

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 simple 2-parameter schema with output schema available, description adequately covers tool scope, parameter semantics, and return format; mentions important service-type constraint but could note behavior when no bids found.

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 has 0% description coverage, so description provides essential compensation: explains keyword maps to bid title (공고명) with 4 examples, and days is search window from today with default value context.

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?

Clear specific verb (Search) + resource (Korean government procurement notices/나라장터), and explicitly distinguishes from siblings by stating it returns BOTH regular bid notices AND preliminary specifications for service-type projects only.

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 concrete examples for keyword parameter ('인공지능', 'AI', etc.) and explicit guidance on days parameter usage (increase for older bids: 30, 60, 90), though lacks explicit comparison to sibling tools analyze_bid_detail and recommend_bids_for_dept.

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