get_supported_languagesDiscover which programming languages have zen rules and detector coverage to identify available best-practice analyses.
Return list of all languages with zen rules and their detector coverage.
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No arguments | |||
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Changes observed during successful MCP inspections.
v0.8.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds the detail that the return includes 'zen rules and their detector coverage', which is content-specific but does not disclose additional behavioral traits such as ordering, pagination, or potential error modes. With annotations present, this is adequate but not rich.
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 a single, concise sentence that front-loads the primary action ('Return list') and specifies what the list contains. There is no redundant information or padding, making it highly 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 that the tool has no parameters, an output schema exists, and the description clearly states the purpose and content, the description is sufficient. It does not need to explain return values because the output schema is provided. The description covers the essential context.
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?
The tool has zero parameters, so the baseline is 4. The description does not need to explain parameters, and the input schema already confirms that no parameters are required. No additional semantic information is needed.
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 uses a specific verb ('Return') and identifies the exact resource ('list of all languages with zen rules and their detector coverage'). This clearly distinguishes it from sibling tools like detect_languages, which likely performs language detection rather than listing supported languages.
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 implies usage (e.g., when you need to know which languages have zen rules), but it does not explicitly state when to use this tool versus alternatives or provide any exclusion criteria. No mention of specific use cases or scenarios is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.