Colombia MCP Server

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

Annotations already provide comprehensive behavioral hints (readOnly, openWorld, idempotent, non-destructive). The description adds useful context about filtering capability and return format (name, community, department), which helps the agent understand what data to expect. However, it doesn't disclose additional behavioral traits like rate limits, authentication needs, or pagination behavior that might be relevant for a list operation.

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 appropriately sized. It starts with the core purpose, explains the optional filtering, specifies return format, and provides concrete usage examples. Every sentence adds value without redundancy. The bilingual presentation (Spanish description with Spanish examples) is consistent and efficient for its intended context.

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 simple read-only list tool with comprehensive annotations and a well-documented single parameter, the description provides adequate context. It covers purpose, filtering capability, and return format. The main gap is the lack of output schema, but the description compensates by specifying what fields to expect. Given the tool's low complexity, this is nearly complete.

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?

With 100% schema description coverage, the schema already fully documents the single optional parameter. The description adds marginal value by mentioning the filtering capability in natural language and providing example usage, but doesn't add semantic details beyond what's in the schema. The baseline of 3 is appropriate when 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: 'Obtiene la lista de resguardos indígenas de Colombia' (Gets the list of indigenous reservations in Colombia). It specifies the exact resource (indigenous reservations) and verb (obtains/list), and distinguishes it from siblings like get_departments or get_natural_areas by focusing on this specific cultural/geographic dataset.

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: when needing indigenous reservation data for Colombia, optionally filtered by department. It includes example queries that demonstrate usage scenarios. However, it doesn't explicitly state when NOT to use it or name specific alternatives among siblings, though the sibling list suggests related geographic tools.

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