Colombia MCP Server

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

Annotations already cover key behavioral traits (read-only, open-world, idempotent, non-destructive), so the bar is lower. The description adds useful context about the return format (list with name, population, postal code) and example queries, but does not disclose additional traits like rate limits, authentication needs, or error handling. No contradiction with annotations exists.

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 and front-loaded with the core purpose, followed by Args, Returns, and usage examples. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 low complexity (one parameter, read-only operation), rich annotations, and no output schema, the description is largely complete. It covers purpose, parameter context, return format, and usage examples. A minor gap is the lack of explicit error handling or edge-case guidance, but overall it provides sufficient context for effective use.

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 100%, providing a clear description of the single parameter (department_id as an integer ID). The description adds minimal value beyond the schema by mentioning the parameter in context but does not elaborate on semantics (e.g., valid ID ranges beyond the schema's minimum). Baseline 3 is appropriate given high schema coverage.

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 specific action ('Obtiene todas las ciudades/municipios') and resource ('de un departamento específico'), distinguishing it from sibling tools like get_department or get_departments. It precisely communicates the tool's function without being vague or tautological.

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 context for when to use this tool (to get cities/municipalities for a specific department), as reinforced by the example usage statements. However, it does not explicitly state when not to use it or name alternatives (e.g., using get_departments first to find department IDs), which prevents a perfect score.

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