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list_languages

Lists available programming languages and their base Nix packages to help developers identify supported options for creating ephemeral development environments.

Instructions

List supported languages and their base Nix packages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the 'list_languages' tool, decorated with @mcp.tool() for registration. It iterates over SUPPORTED_LANGUAGES to generate a formatted list of supported languages and their base packages.
    @mcp.tool()
    def list_languages() -> str:
        """List supported languages and their base Nix packages."""
        lines = []
        for key, profile in SUPPORTED_LANGUAGES.items():
            base = ", ".join(profile.base_packages)
            lines.append(f"- {key}: {profile.label} (base: {base})")
        return "\n".join(lines)
  • Dictionary defining the supported languages, their labels, and base Nix packages, used by the list_languages handler.
    SUPPORTED_LANGUAGES: dict[str, LanguageProfile] = {
        # Interpreted runtimes where we can build an env via withPackages.
        "python": LanguageProfile(label="Python 3.13", base_packages=["python313"]),
        "ruby": LanguageProfile(label="Ruby 3.3", base_packages=["ruby_3_3"]),
        "r": LanguageProfile(label="R", base_packages=["R"]),
        "lua": LanguageProfile(label="Lua 5.4", base_packages=["lua5_4"]),
    }
  • Dataclass defining the structure for language profiles used in SUPPORTED_LANGUAGES.
    @dataclass(frozen=True)
    class LanguageProfile:
        label: str
        base_packages: List[str]
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how it behaves—e.g., whether it returns all languages at once, if there's pagination, error conditions, or performance characteristics. This leaves significant behavioral aspects unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any extraneous information. It is appropriately sized and front-loaded, making it easy to understand at a glance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, has output schema), the description is adequate but minimal. It covers the basic purpose but lacks usage guidelines and behavioral details, which are important even for simple tools. The presence of an output schema reduces the need to describe return values, but other contextual gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics, but with no parameters, this is acceptable, warranting a baseline score of 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and the resource ('supported languages and their base Nix packages'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from the sibling tool 'run_in_env_impl', which appears to serve a different function (execution vs. listing).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 or in what context it should be invoked. With a sibling tool present, this lack of comparative usage information is a notable gap.

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

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