Agent Fails Silently — No Error Logging Makes Debugging Impossible

Symptom

Agent task appears to run but produces no output
No error message in logs — just silence
except Exception: pass swallowing all errors
User reports “it stopped working” — no information to debug
Works in development, fails silently in production

Root Cause

Broad exception handlers that suppress errors, missing logging setup, or bare try/except blocks without logging. In async code, unhandled exceptions in tasks are silently swallowed unless explicitly logged or awaited.

Fix

Option 1: Never suppress exceptions without logging

import logging, traceback

logger = logging.getLogger(__name__)

# WRONG — exception swallowed, no trace
try:
    result = await process_task(task)
except Exception:
    pass  # Silent failure

# WRONG — printed but not logged, lost in production
try:
    result = await process_task(task)
except Exception as e:
    print(f"Error: {e}")  # Not in log aggregator

# RIGHT — logged with full context
try:
    result = await process_task(task)
except Exception as e:
    logger.exception(  # Logs error + full stack trace
        f"Task failed: task_id={task.id} type={task.type}",
        extra={"task_id": task.id, "task_type": task.type}
    )
    raise  # Re-raise so caller knows it failed

Option 2: Structured logging setup

import logging, json, sys
from datetime import datetime

def setup_logging(level: str = "INFO"):
    """Configure structured JSON logging for production"""
    class JSONFormatter(logging.Formatter):
        def format(self, record):
            log_entry = {
                "timestamp": datetime.utcnow().isoformat() + "Z",
                "level": record.levelname,
                "logger": record.name,
                "message": record.getMessage(),
                "module": record.module,
                "function": record.funcName,
                "line": record.lineno,
            }
            if record.exc_info:
                log_entry["exception"] = self.formatException(record.exc_info)
            if hasattr(record, "task_id"):
                log_entry["task_id"] = record.task_id
            return json.dumps(log_entry)

    handler = logging.StreamHandler(sys.stdout)
    handler.setFormatter(JSONFormatter())

    root_logger = logging.getLogger()
    root_logger.addHandler(handler)
    root_logger.setLevel(getattr(logging, level.upper()))

setup_logging("INFO")

Option 3: Catch and log unhandled asyncio task exceptions

import asyncio, logging

logger = logging.getLogger(__name__)

def handle_task_exception(task: asyncio.Task):
    """Called when a task raises an unhandled exception"""
    if task.cancelled():
        return
    exc = task.exception()
    if exc is not None:
        logger.exception(
            f"Unhandled exception in task {task.get_name()}",
            exc_info=(type(exc), exc, exc.__traceback__)
        )

async def create_monitored_task(coro, name: str = None) -> asyncio.Task:
    """Create task with error monitoring"""
    task = asyncio.create_task(coro, name=name)
    task.add_done_callback(handle_task_exception)
    return task

# Global handler for all unhandled exceptions
def setup_asyncio_exception_handler():
    loop = asyncio.get_event_loop()
    def handler(loop, context):
        exc = context.get("exception")
        if exc:
            logger.exception(
                f"Unhandled asyncio exception: {context.get('message')}",
                exc_info=(type(exc), exc, exc.__traceback__)
            )
        else:
            logger.error(f"Asyncio error: {context.get('message')}")
    loop.set_exception_handler(handler)

Option 4: Decorator for automatic error logging

import functools, logging, time
from typing import Callable, TypeVar

logger = logging.getLogger(__name__)
T = TypeVar("T")

def log_errors(func: Callable) -> Callable:
    """Decorator: log any exception with context before re-raising"""
    @functools.wraps(func)
    async def async_wrapper(*args, **kwargs):
        start = time.time()
        try:
            result = await func(*args, **kwargs)
            elapsed = time.time() - start
            logger.debug(f"{func.__name__} succeeded in {elapsed:.2f}s")
            return result
        except Exception as e:
            elapsed = time.time() - start
            logger.exception(
                f"{func.__name__} failed after {elapsed:.2f}s: {type(e).__name__}: {e}"
            )
            raise

    @functools.wraps(func)
    def sync_wrapper(*args, **kwargs):
        start = time.time()
        try:
            result = func(*args, **kwargs)
            return result
        except Exception as e:
            elapsed = time.time() - start
            logger.exception(
                f"{func.__name__} failed after {elapsed:.2f}s: {type(e).__name__}: {e}"
            )
            raise

    if asyncio.iscoroutinefunction(func):
        return async_wrapper
    return sync_wrapper

# Usage
@log_errors
async def process_agent_task(task: dict) -> dict:
    return await do_work(task)

Option 5: Context-rich error logging

import logging
from contextlib import asynccontextmanager

logger = logging.getLogger(__name__)

@asynccontextmanager
async def task_context(task_id: str, task_type: str, **extra):
    """Context manager that enriches all logs and catches errors"""
    log_context = {"task_id": task_id, "task_type": task_type, **extra}
    logger.info(f"Task started", extra=log_context)

    try:
        yield log_context
        logger.info(f"Task completed successfully", extra=log_context)
    except Exception as e:
        logger.exception(
            f"Task failed: {type(e).__name__}: {e}",
            extra={**log_context, "error_type": type(e).__name__, "error": str(e)}
        )
        raise

# Usage
async def run_task(task):
    async with task_context(task["id"], task["type"], user_id=task["user_id"]):
        result = await process(task)
        return result

Option 6: Alert on error rate increase

import time
from collections import deque

class ErrorRateMonitor:
    def __init__(self, window_seconds: int = 60, threshold: float = 0.1):
        self.window = window_seconds
        self.threshold = threshold
        self.events = deque()  # (timestamp, is_error)

    def record(self, is_error: bool):
        now = time.time()
        self.events.append((now, is_error))
        self._cleanup(now)

        error_rate = self._error_rate()
        if error_rate > self.threshold:
            logger.warning(
                f"High error rate: {error_rate:.0%} in last {self.window}s",
                extra={"error_rate": error_rate, "window_seconds": self.window}
            )

    def _cleanup(self, now: float):
        cutoff = now - self.window
        while self.events and self.events[0][0] < cutoff:
            self.events.popleft()

    def _error_rate(self) -> float:
        if not self.events:
            return 0.0
        errors = sum(1 for _, is_error in self.events if is_error)
        return errors / len(self.events)

monitor = ErrorRateMonitor(window_seconds=60, threshold=0.1)

Logging Levels Reference

Level	Use for
`DEBUG`	Detailed trace info (tool calls, API requests)
`INFO`	Task start/completion, state transitions
`WARNING`	Recoverable issues, rate limit approaching
`ERROR`	Task failed but system running
`CRITICAL`	System-level failure, immediate action needed

Expected Token Savings

Debugging silent failure without logs: ~15,000 tokens (extensive investigation) Comprehensive logging: error diagnosed in seconds from logs

Environment

All production agent deployments
Source: direct experience; the single most common cause of long debugging sessions

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