SonarQube MCP Server

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

Annotations cover key behavioral traits: read-only, non-destructive, idempotent, and closed-world. The description adds context by specifying it retrieves 'description and metadata,' which clarifies the scope of data returned. However, it does not disclose additional behaviors like rate limits, authentication needs, or error handling, leaving some gaps despite annotations.

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 well-structured, with a clear purpose statement followed by parameter details in a separate 'Args' section. Every sentence adds value, and there is no unnecessary information. It could be slightly improved by integrating the parameter explanation more seamlessly, but overall it is efficient.

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 (1 parameter), rich annotations, and presence of an output schema, the description is reasonably complete. It explains what the tool does and provides parameter semantics, which compensates for the low schema coverage. However, it lacks usage guidelines and could better integrate with sibling tools, leaving minor gaps.

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 0%, so the description must compensate. It provides a clear example for the 'rule_key' parameter ('e.g., python:S1192, java:S106'), adding meaningful semantics beyond the schema's basic type definition. This effectively explains the parameter's format and usage, though it could benefit from more detail on valid rule keys.

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: 'Get the description and metadata for a SonarQube rule.' It specifies the verb ('Get') and resource ('description and metadata for a SonarQube rule'), making it easy to understand what the tool does. However, it does not explicitly differentiate from sibling tools like 'get_issue' or 'get_project_metrics', which might also retrieve metadata, so it misses full sibling differentiation.

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 no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'get_issue' or 'search_issues', nor does it specify contexts or exclusions for usage. The only implied usage is retrieving rule details, but this is insufficient for effective tool selection.

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