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instrumentedTest

Run instrumented tests for Android projects to verify app behavior on devices or emulators. Specify the project folder path to execute tests that interact with the Android framework.

Instructions

Run instrumented test for the Android project in the folder

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
folderYesThe full path of the current folder that the Android project sits

Implementation Reference

  • The shared handler function for all tools, including 'instrumentedTest', which parses arguments, sets the command to run 'instrumentedTest.sh', executes it via subprocess, and processes output to extract errors or success message.
    @server.call_tool()
    async def call_tool(name, arguments: dict) -> list[TextContent]:
        try:
            args = Folder(**arguments)
        except ValueError as e:
            raise McpError(ErrorData(code=INVALID_PARAMS, message=str(e)))
        # os.chdir(args.folder)
        script_dir = os.path.dirname(os.path.abspath(__file__))
    
        command = [""]
        if name == "build":
            command = [os.path.join(script_dir, "build.sh"), args.folder]
        elif name == "test":
            command = [os.path.join(script_dir, "test.sh"), args.folder]
        else:
            command = [os.path.join(script_dir, "instrumentedTest.sh"), args.folder]
    
        result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=False)
        stdout_lines = result.stdout.decode("utf-8").splitlines()
        stderr_lines = result.stderr.decode("utf-8").splitlines()
        all_lines = stdout_lines + stderr_lines
        
        
        error_lines = [line for line in all_lines if "failure: " in line.lower() or "e: " in line.lower() or " failed" in line.lower()]
        error_message = "\n".join(error_lines)
        if not error_message:
            error_message = "Successful"
        return [
            TextContent(type="text", text=f"{error_message}")
            ]
  • Registration of the 'instrumentedTest' tool in the list_tools() function, specifying name, description, and input schema.
    Tool(
        name="instrumentedTest",
        description="Run instrumented test for the Android project in the folder",
        inputSchema=Folder.model_json_schema(),
    )
  • Pydantic BaseModel defining the input parameters for the 'instrumentedTest' tool (and others), consisting of a single 'folder' field.
    class Folder(BaseModel):
        """Parameters"""
        folder: Annotated[str, Field(description="The full path of the current folder that the Android project sits")]
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but reveals nothing about execution characteristics: whether it's read-only or mutating, what permissions are needed, how long it runs, what happens on failure, or what output to expect. For a test execution tool with zero annotation coverage, this is a significant gap in transparency.

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 gets straight to the point with no wasted words. It's appropriately sized for a single-parameter tool and front-loads the essential information. Every word earns its place in this concise formulation.

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 this is a test execution tool with no annotations, no output schema, and behavioral unknowns, the description is insufficiently complete. It doesn't explain what 'instrumented test' means in practice, what the tool actually does during execution, what results to expect, or how it differs from the sibling 'test' tool. For a potentially complex operation like Android testing, more context is needed.

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 schema description coverage is 100%, with the single parameter 'folder' well-documented in the schema as 'The full path of the current folder that the Android project sits'. The description adds no additional parameter information beyond what's already in the schema. With complete schema coverage, the baseline score of 3 is appropriate.

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 ('Run instrumented test') and the target ('for the Android project in the folder'), making the purpose understandable. It distinguishes from sibling tools 'build' and 'test' by specifying 'instrumented test', which suggests a more specific type of testing than generic 'test'. However, it doesn't fully explain what an 'instrumented test' entails compared to other test types.

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 the sibling 'test' tool. It implies usage for Android projects in a folder, but doesn't specify prerequisites, when instrumented tests are appropriate, or any exclusions. This leaves the agent with little context for choosing between available testing options.

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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