Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add EngineerWithAI/engineerwith-agents --skill error-handling-patternsgit clone --depth 1 https://github.com/EngineerWithAI/engineerwith-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/engineerwithai/engineerwith-agents/error-handling-patterns)<a href="https://agentmods.dev/skills/engineerwithai/engineerwith-agents/error-handling-patterns"><img src="https://agentmods.dev/badge/skills/engineerwithai/engineerwith-agents/error-handling-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/engineerwithai/engineerwith-agents/error-handling-patterns"><img src="https://agentmods.dev/badge/skills/engineerwithai/engineerwith-agents/error-handling-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.03840 |
| Opus 5.5 | $0.00017 | $0.01536 |
| Sonnet 5.5 | $0.00009 | $0.00768 |
| Haiku 4.5 | $0.00004 | $0.00384 |
Grade A, and why
error-handling-patterns scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(url, timeout=5) This is a copy
100% identical to error-handling-patterns — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 637 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Error Handling Patterns
Build resilient applications with robust error handling strategies that gracefully handle failures and provide excellent debugging experiences.
When to Use This Skill
- Implementing error handling in new features
- Designing error-resilient APIs
- Debugging production issues
- Improving application reliability
- Creating better error messages for users and developers
- Implementing retry and circuit breaker patterns
- Handling async/concurrent errors
- Building fault-tolerant distributed systems
Core Concepts
1. Error Handling Philosophies
Exceptions vs Result Types:
- Exceptions: Traditional try-catch, disrupts control flow
- Result Types: Explicit success/failure, functional approach
- Error Codes: C-style, requires discipline
- Option/Maybe Types: For nullable values
When to Use Each:
- Exceptions: Unexpected errors, exceptional conditions
- Result Types: Expected errors, validation failures
- Panics/Crashes: Unrecoverable errors, programming bugs
2. Error Categories
Recoverable Errors:
- Network timeouts
- Missing files
- Invalid user input
- API rate limits
Unrecoverable Errors:
- Out of memory
- Stack overflow
- Programming bugs (null pointer, etc.)
Language-Specific Patterns
Python Error Handling
Custom Exception Hierarchy:
class ApplicationError(Exception):
"""Base exception for all application errors."""
def __init__(self, message: str, code: str = None, details: dict = None):
super().__init__(message)
self.code = code
self.details = details or {}
self.timestamp = datetime.utcnow()
class ValidationError(ApplicationError):
"""Raised when validation fails."""
pass
class NotFoundError(ApplicationError):
"""Raised when resource not found."""
pass
class ExternalServiceError(ApplicationError):
"""Raised when external service fails."""
def __init__(self, message: str, service: str, **kwargs):
super().__init__(message, **kwargs)
self.service = service
# Usage
def get_user(user_id: str) -> User:
user = db.query(User).filter_by(id=user_id).first()
if not user:
raise NotFoundError(
f"User not found",
code="USER_NOT_FOUND",
details={"user_id": user_id}
)
return user
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 637 lines · 43 tokens per session scan A aa8f11361c89
error-handling-patterns is a skill published in the GitHub repository EngineerWithAI/engineerwith-agents (4 stars, last pushed 9mo ago), licensed MIT. It adds 43 tokens to every session and 3,840 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to error-handling-patterns, differing in 0 lines, and is treated as a copy.
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