Error Handling logo

Error Handling

CommunityPopular
CloudAI-X
error-handling

Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.

Overview

PublisherCloudAI-X
Repositoryclaude-workflow-v2
Skill nameerror-handling
Stars
1.4K
Forks
188
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by CloudAI-X on GitHub. Read the source before you install it.

Installation

Install the Error Handling AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/CloudAI-X/claude-workflow-v2.git /tmp/claude-workflow-v2
mkdir -p .claude/skills
cp -r /tmp/claude-workflow-v2/skills/error-handling .claude/skills/error-handling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Error Handling in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Error Handling on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Error Handling is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Error Handling & Observability

When to Load

  • Trigger: Try/catch patterns, retry logic, error responses, circuit breakers, structured logging
  • Skip: No error handling or observability involved in the current task

Error Handling Workflow

Copy this checklist and track progress:

Error Handling Progress:
- [ ] Step 1: Define error taxonomy (categories and severity)
- [ ] Step 2: Implement error handling by layer
- [ ] Step 3: Set up structured logging
- [ ] Step 4: Add retry and circuit breaker patterns
- [ ] Step 5: Configure error tracking service
- [ ] Step 6: Define user-facing error messages
- [ ] Step 7: Validate against anti-patterns checklist

Error Handling Patterns by Language

JavaScript / TypeScript

typescript
// Custom error hierarchy
class AppError extends Error {
  constructor(
    message: string,
    public statusCode: number = 500,
    public code: string = "INTERNAL_ERROR",
    public isOperational: boolean = true,
  ) {
    super(message);
    this.name = this.constructor.name;
  }
}
class NotFoundError extends AppError {
  constructor(resource: string, id: string) {
    super(`${resource} with id ${id} not found`, 404, "NOT_FOUND");
  }
}
class ValidationError extends AppError {
  constructor(public errors: Record<string, string[]>) {
    super("Validation failed", 400, "VALIDATION_ERROR");
  }
}

// WRONG: Swallowing errors silently
try {
  await saveUser(data);
} catch (e) {
  // nothing here -- bug hides forever
}

// WRONG: Catching and re-throwing without context
try {
  await saveUser(data);
} catch (e) {
  throw e; // pointless try/catch
}

// CORRECT: Add context, handle or propagate
try {
  await saveUser(data);
} catch (error) {
  if (error instanceof ValidationError) {
    return res.status(400).json({ errors: error.errors });
  }
  logger.error("Failed to save user", { error, userId: data.id });
  throw new AppError("Unable to save user", 500, "USER_SAVE_FAILED");
}

Express Global Error Handler

typescript
// Centralized error handler middleware (must have 4 params)
app.use((err: Error, req: Request, res: Response, next: NextFunction) => {
  if (err instanceof AppError) {
    logger.warn("Operational error", {
      code: err.code,
      statusCode: err.statusCode,
      path: req.path,
    });
    return res.status(err.statusCode).json({
      error: { code: err.code, message: err.message },
    });
  }

  // Unexpected errors -- these are bugs
  logger.error("Unexpected error", {
    error: err.message,
    stack: err.stack,
    path: req.path,
  });
  res.status(500).json({
    error: { code: "INTERNAL_ERROR", message: "An unexpected error occurred" },
  });
});

Python

python
# Custom exception hierarchy
class AppError(Exception):
    def __init__(self, message: str, code: str = "INTERNAL_ERROR", status: int = 500):
        self.message = message
        self.code = code
        self.status = status
        super().__init__(message)

class NotFoundError(AppError):
    def __init__(self, resource: str, id: str):
        super().__init__(f"{resource} {id} not found", "NOT_FOUND", 404)

class ValidationError(AppError):
    def __init__(self, errors: dict[str, list[str]]):
        self.errors = errors
        super().__init__("Validation failed", "VALIDATION_ERROR", 400)

# WRONG: Bare except
try:
    result = process(data)
except:  # catches SystemExit, KeyboardInterrupt too!
    pass

# CORRECT: Specific exceptions, proper logging
try:
    result = process(data)
except ValidationError as e:
    logger.warning("Validation failed", extra={"errors": e.errors})
    raise
except DatabaseError as e:
    logger.error("Database error during processing", exc_info=True)
    raise AppError("Processing failed", "PROCESS_FAILED") from e

Go

go
// Define sentinel errors and custom types
var (
    ErrNotFound     = errors.New("resource not found")
    ErrUnauthorized = errors.New("unauthorized")
)

type ValidationError struct {
    Field   string
    Message string
}

func (e *ValidationError) Error() string {
    return fmt.Sprintf("validation: %s - %s", e.Field, e.Message)
}

// WRONG: Ignoring errors
data, _ := json.Marshal(user)  // error silently dropped

// WRONG: Only returning error string
if err != nil {
    return fmt.Errorf("failed: %s", err.Error())  // loses error chain
}

// CORRECT: Wrap errors with context
if err != nil {
    return fmt.Errorf("saving user %s: %w", user.ID, err)  // %w preserves chain
}

// CORRECT: Check error types
if errors.Is(err, ErrNotFound) {
    http.Error(w, "Not found", http.StatusNotFound)
    return
}
var valErr *ValidationError
if errors.As(err, &valErr) {
    http.Error(w, valErr.Error(), http.StatusBadRequest)
    return
}

Structured Logging

JSON Log Format

typescript
// WRONG: Unstructured string logs
console.log(`User ${userId} created order ${orderId} at ${new Date()}`);
// Impossible to parse, filter, or aggregate

// CORRECT: Structured JSON logs
import pino from "pino";

const logger = pino({
  level: process.env.LOG_LEVEL || "info",
  formatters: {
    level: (label) => ({ level: label }),
  },
  redact: ["req.headers.authorization", "password", "ssn"],
});
logger.info({
  event: "order_created",
  userId: "123",
  orderId: "456",
  amount: 99.99,
  currency: "USD",
});
// Output: {"level":"info","event":"order_created","userId":"123","orderId":"456",...}

Correlation IDs

typescript
// Middleware to propagate correlation ID across requests
import { randomUUID } from "crypto";
import { AsyncLocalStorage } from "async_hooks";

const asyncStorage = new AsyncLocalStorage<{ correlationId: string }>();

app.use((req, res, next) => {
  const correlationId =
    (req.headers["x-correlation-id"] as string) || randomUUID();
  res.setHeader("x-correlation-id", correlationId);

  asyncStorage.run({ correlationId }, () => next());
});

// Logger automatically includes correlation ID
function getLogger() {
  const store = asyncStorage.getStore();
  return logger.child({ correlationId: store?.correlationId });
}

// Usage in any handler or service
const log = getLogger();
log.info({ event: "payment_processed", amount: 50 });
// Output includes correlationId automatically

Log Levels Guide

TRACE: Extremely detailed (loop iterations, variable values)  -- dev only
DEBUG: Diagnostic info (function entry/exit, state changes)   -- dev/staging
INFO:  Normal operations (request handled, job completed)     -- all envs
WARN:  Unexpected but recoverable (retry succeeded, fallback used)
ERROR: Operation failed (unhandled exception, service down)
FATAL: Application cannot continue (missing config, DB unreachable)

Production default: INFO
Never log: passwords, tokens, PII, credit cards, full request bodies

Error Boundaries and Graceful Degradation

React Error Boundary

tsx
class ErrorBoundary extends React.Component<
  { fallback: React.ReactNode; children: React.ReactNode },
  { hasError: boolean; error?: Error }
> {
  state = { hasError: false, error: undefined };
  static getDerivedStateFromError(error: Error) {
    return { hasError: true, error };
  }
  componentDidCatch(error: Error, info: React.ErrorInfo) {
    logger.error("React error boundary caught error", {
      error: error.message,
      componentStack: info.componentStack,
    });
  }
  render() {
    return this.state.hasError ? this.props.fallback : this.props.children;
  }
}

// Usage: wrap sections independently
<ErrorBoundary fallback={<p>Dashboard unavailable</p>}>
  <Dashboard />
</ErrorBoundary>
<ErrorBoundary fallback={<p>Sidebar unavailable</p>}>
  <Sidebar />
</ErrorBoundary>

Service Degradation

typescript
// Graceful degradation: serve stale data when service is down
async function getProductRecommendations(userId: string) {
  try {
    return await recommendationService.get(userId);
  } catch (error) {
    logger.warn("Recommendation service unavailable, using fallback", {
      userId,
      error: error.message,
    });
    return getCachedRecommendations(userId) || getDefaultRecommendations();
  }
}

Retry Patterns

Exponential Backoff

typescript
async function withRetry<T>(
  fn: () => Promise<T>,
  options: {
    maxRetries?: number;
    baseDelay?: number;
    maxDelay?: number;
    retryOn?: (error: Error) => boolean;
  } = {},
): Promise<T> {
  const {
    maxRetries = 3,
    baseDelay = 1000,
    maxDelay = 30000,
    retryOn,
  } = options;
  for (let attempt = 0; attempt <= maxRetries; attempt++) {
    try {
      return await fn();
    } catch (error) {
      if (attempt === maxRetries) throw error;
      if (retryOn && !retryOn(error as Error)) throw error;

      const delay = Math.min(
        baseDelay * 2 ** attempt + Math.random() * 1000,
        maxDelay,
      );
      logger.warn("Retrying operation", { attempt: attempt + 1, delay });
      await new Promise((r) => setTimeout(r, delay));
    }
  }
  throw new Error("Unreachable");
}

// Usage: retry only on transient errors
const data = await withRetry(() => fetch("https://api.example.com/data"), {
  retryOn: (err) => err.message.includes("ECONNRESET"),
});

Circuit Breaker

typescript
class CircuitBreaker {
  private failures = 0;
  private lastFailure = 0;
  private state: "closed" | "open" | "half-open" = "closed";

  constructor(
    private threshold: number = 5,
    private resetTimeout: number = 60000,
  ) {}

  async execute<T>(fn: () => Promise<T>, fallback?: () => T): Promise<T> {
    if (this.state === "open") {
      if (Date.now() - this.lastFailure > this.resetTimeout) {
        this.state = "half-open";
      } else {
        if (fallback) return fallback();
        throw new Error("Circuit breaker is open");
      }
    }

    try {
      const result = await fn();
      this.failures = 0;
      this.state = "closed";
      return result;
    } catch (error) {
      this.failures++;
      this.lastFailure = Date.now();
      if (this.failures >= this.threshold) this.state = "open";
      if (fallback) return fallback();
      throw error;
    }
  }
}

// Usage: trips open after 5 failures, resets after 30s
const paymentCircuit = new CircuitBreaker(5, 30000);
const result = await paymentCircuit.execute(
  () => paymentService.charge(amount),
  () => ({ queued: true, message: "Payment will be processed shortly" }),
);

Error Tracking Integration

Sentry Setup

typescript
import * as Sentry from "@sentry/node";

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  environment: process.env.NODE_ENV,
  tracesSampleRate: process.env.NODE_ENV === "production" ? 0.1 : 1.0,
  beforeSend(event) {
    // Scrub sensitive data
    if (event.request?.headers) delete event.request.headers["authorization"];
    return event;
  },
});

Sentry.setUser({ id: user.id, email: user.email });
Sentry.captureException(error, {
  tags: { subsystem: "payment", provider: "stripe" },
  extra: { orderId, amount },
});

User-Facing vs Internal Errors

typescript
// Map internal errors to user-friendly messages
const USER_MESSAGES: Record<string, string> = {
  VALIDATION_ERROR: "Please check your input and try again.",
  NOT_FOUND: "The requested resource could not be found.",
  RATE_LIMITED: "Too many requests. Please wait a moment.",
  PAYMENT_FAILED: "Payment could not be processed. Please try another method.",
  INTERNAL_ERROR: "Something went wrong. Please try again later.",
};

function toUserResponse(error: AppError) {
  return {
    error: {
      code: error.code,
      message: USER_MESSAGES[error.code] || USER_MESSAGES["INTERNAL_ERROR"],
    },
  };
}

// WRONG: Exposing internal details to users
res.status(500).json({
  error: 'QueryFailedError: relation "users" does not exist',
  stack: error.stack,
});

// CORRECT: Generic message to user, full details in logs
logger.error("Database query failed", {
  error: error.message,
  stack: error.stack,
  query,
});
res.status(500).json(toUserResponse(new AppError("DB error", 500)));

Common Anti-Patterns Summary

AVOID                              DO INSTEAD
-------------------------------------------------------------------
Empty catch blocks                 Log and handle or re-throw
Bare `except:` in Python           Catch specific exceptions
console.log for production         Structured logger (pino, winston)
Logging passwords/tokens           Redact sensitive fields
Retry without backoff              Exponential backoff with jitter
Retry on all errors                Only retry transient/network errors
No circuit breaker                 Circuit breaker for external calls
Exposing stack traces to users     Generic user messages, detailed logs
No correlation IDs                 Propagate correlation ID across services
One giant try/catch                Granular error handling per operation
Logging inside tight loops         Log summaries/aggregates
No error boundaries in React       Wrap independent sections separately

Frequently asked questions

What does the Error Handling AI skill do?

Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.

Why use Error Handling on TypingMind?

Because you install it once and use it with any model. Error Handling is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Error Handling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CloudAI-X/claude-workflow-v2/tree/main/skills/error-handling. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Error Handling?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Error Handling?

As many as you like. As long as a model supports skills, you can use Error Handling with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Error Handling AI skill free?

Yes. It is published on GitHub by CloudAI-X under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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