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local_dev_from_github

Create local development environments from GitHub repositories to run tests and check code coverage in sandboxed setups.

Instructions

Create a new local development environment from a GitHub repository

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
github_urlYesGitHub repository URL

Implementation Reference

  • Tool handler in call_tool function: checks tool name, calls create_environment_from_github with github_url argument, constructs success response with environment details.
    if name == "local_dev_from_github":
        logger.debug("Creating environment from GitHub")
        env = await create_environment_from_github(arguments["github_url"])
        result = {
            "success": True,
            "data": {
                "id": env.id,
                "working_dir": str(env.sandbox.work_dir),
                "created_at": env.created_at.isoformat(),
                "runtime": env.runtime_config.name.value,
            },
        }
        logger.debug(f"Environment created successfully: {result}")
        return [types.TextContent(type="text", text=json.dumps(result))]
  • Input schema defining the required 'github_url' parameter.
    inputSchema={
        "type": "object",
        "properties": {
            "github_url": {"type": "string", "description": "GitHub repository URL"}
        },
        "required": ["github_url"],
    },
  • Registration of the tool in the global tools list used by list_tools().
    types.Tool(
        name="local_dev_from_github",
        description="Create a new local development environment from a GitHub repository",
        inputSchema={
            "type": "object",
            "properties": {
                "github_url": {"type": "string", "description": "GitHub repository URL"}
            },
            "required": ["github_url"],
        },
    ),
  • Helper function implementing the core logic: clones GitHub repository into a temporary staging sandbox, creates the environment from the cloned path, and cleans up staging.
    async def create_environment_from_github(
        github_url: str, branch: Optional[str] = None
    ) -> Environment:
        """Create new environment from GitHub repository."""
        staging = await create_sandbox("mcp-staging-")
        try:
            repo = await clone_github_repository(staging, github_url, branch)
            env = await create_environment_from_path(repo)
            return env
        finally:
            cleanup_sandbox(staging)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a local dev environment but lacks details on permissions needed, whether it overwrites existing environments, error handling, or output format. This is a significant gap for a creation tool with zero annotation coverage.

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, clear sentence with zero wasted words, making it highly efficient and front-loaded. It directly communicates the core functionality without unnecessary elaboration.

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

Completeness2/5

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

Given the tool's complexity as a creation operation with no annotations and no output schema, the description is insufficient. It doesn't explain what the created environment entails, how to interact with it, or potential side effects, leaving critical gaps for an AI agent to use it effectively.

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

Parameters3/5

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

The input schema has 100% description coverage, with the single parameter 'github_url' documented as 'GitHub repository URL'. The description adds no additional semantic context beyond this, such as URL format examples or validation rules, so it meets the baseline for high schema coverage.

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 ('Create') and resource ('local development environment from a GitHub repository'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'local_dev_from_filesystem' or 'local_dev_cleanup', which would require mentioning the specific GitHub source distinction.

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 like 'local_dev_from_filesystem' or 'local_dev_cleanup', nor does it mention prerequisites or exclusions. It merely states what the tool does without contextual usage information.

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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