analyze_tests
Analyze recent test runs to identify failures and provide detailed diagnostics, enabling developers to troubleshoot issues efficiently.
Instructions
Analyze the most recent test run and provide detailed information about failures.
Args:
summary_only: Whether to return only a summary of the test results
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| summary_only | No |
Implementation Reference
- The primary handler for the 'analyze_tests' tool. Decorated with @mcp.tool() for registration. Reads the test log file, parses it using the helper analyze_pytest_log_content, augments with metadata, and returns structured results or errors.@mcp.tool() async def analyze_tests(summary_only: bool = False) -> dict[str, Any]: """Analyze the most recent test run and provide detailed information about failures. Args: summary_only: Whether to return only a summary of the test results """ logger.info("Analyzing test results (summary_only=%s)...", summary_only) log_file = test_log_file if not os.path.exists(log_file): error_msg = f"Test log file not found at: {log_file}. Please run tests first." logger.error(error_msg) return {"error": error_msg, "summary": {"status": "ERROR", "passed": 0, "failed": 0, "skipped": 0}} try: with open(log_file, encoding="utf-8", errors="ignore") as f: log_contents = f.read() if not log_contents.strip(): error_msg = f"Test log file is empty: {log_file}" logger.warning(error_msg) return {"error": error_msg, "summary": {"status": "EMPTY", "passed": 0, "failed": 0, "skipped": 0}} analysis = analyze_pytest_log_content(log_contents, summary_only=summary_only) # Add metadata similar to the old analyze_test_log function log_time = datetime.fromtimestamp(os.path.getmtime(log_file)) time_elapsed = (datetime.now() - log_time).total_seconds() / 60 # minutes analysis["log_file"] = log_file analysis["log_timestamp"] = log_time.isoformat() analysis["log_age_minutes"] = round(time_elapsed, 1) # The analyze_pytest_log_content already returns a structure including 'overall_summary'. # If summary_only is true, it returns only that. Otherwise, it returns more details. # We can directly return this analysis dictionary. # Ensure there's always a summary structure for consistent access, even if minimal if "overall_summary" not in analysis: analysis["overall_summary"] = {"status": "UNKNOWN", "passed": 0, "failed": 0, "skipped": 0} if "summary" not in analysis: # for backward compatibility or general access analysis["summary"] = analysis["overall_summary"] logger.info( "Test log analysis completed using test_log_parser. Summary status: %s", analysis.get("summary", {}).get("status"), ) return analysis except Exception as e: # pylint: disable=broad-exception-caught error_msg = f"Error analyzing test log file with test_log_parser: {e}" logger.error(error_msg, exc_info=True) return {"error": error_msg, "summary": {"status": "ERROR", "passed": 0, "failed": 0, "skipped": 0}}
- Pydantic input schema/model for the analyze_tests tool, defining the optional summary_only parameter.class AnalyzeTestsInput(BaseModel): """Parameters for analyzing tests.""" summary_only: bool = Field(default=False, description="Whether to return only a summary of the test results")
- Key helper function implementing the pytest log parsing logic. Extracts overall summary and list of failed tests using sub-helpers extract_overall_summary and extract_failed_tests. Invoked by the main handler.def analyze_pytest_log_content(log_contents: str, summary_only: bool = False) -> Dict[str, Any]: """ Analyzes the full string content of a pytest log. Args: log_contents: The string content of the pytest log. summary_only: If True, returns only the overall summary. Otherwise, includes details like failed tests. Returns: A dictionary containing the analysis results. """ overall_summary = extract_overall_summary(log_contents) if summary_only: return {"overall_summary": overall_summary} failed_tests = extract_failed_tests(log_contents) # Placeholder for other details to be added once their extraction functions are moved/implemented # error_details = extract_error_details(log_contents) # exception_traces = extract_exception_traces(log_contents) # module_statistics = extract_module_statistics(log_contents) return { "overall_summary": overall_summary, "failed_tests": failed_tests, # "error_details": error_details, # Uncomment when available # "exception_traces": exception_traces, # Uncomment when available # "module_statistics": module_statistics, # Uncomment when available }