error-patterns
SkillAI & modelsProvides error classification, recovery, and graceful-degradation patterns. Use when implementing error handling or debugging resilience failures in any skill.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the error-patterns skill
What this skill tells your AI
The instructions your AI receives, as published by athola/claude-night-market in plugins/leyline/skills/error-patterns/SKILL.md and read by ahel’s review.
Table of Contents
- Overview
- When to Use
- Error Classification
- By Severity
- By Recoverability
- Quick Start
- Standard Error Handler
- Error Result
- Common Patterns
- Authentication Errors (401/403)
- Rate Limit Errors (429)
- Timeout Errors
- Context Too Large (400)
- Integration Pattern
- Detailed Resources
- Exit Criteria
Error Patterns
Overview
Standardized error handling patterns for consistent, production-grade behavior across plugins. Provides error classification, recovery strategies, and debugging workflows.
When To Use
- Building resilient integrations
- Need consistent error handling
- Want graceful degradation
- Debugging production issues
When NOT To Use
- Project doesn't use the leyline infrastructure patterns
- Simple scripts without service architecture needs
Error Classification
By Severity
| Level | Action | Example |
|---|---|---|
| Critical | Halt, alert | Auth failure, service down |
| Error | Retry or secondary strategy | Rate limit, timeout |
| Warning | Log, continue | Partial results, deprecation |
| Info | Log only | Non-blocking issues |
By Recoverability
class ErrorCategory(Enum):
TRANSIENT = "transient" # Retry likely to succeed
PERMANENT = "permanent" # Retry won't help
CONFIGURATION = "config" # User action needed
RESOURCE = "resource" # Quota/limit issue
Verification: Run the command with --help flag to verify availability.
Quick Start
Standard Error Handler
from leyline.error_patterns import handle_error, ErrorCategory
try:
result = service.execute(prompt)
except RateLimitError as e:
return handle_error(
e, ErrorCategory.RESOURCE, {"retry_after": e.retry_after, "service": "gemini"}
)
except AuthError as e:
return handle_error(
e, ErrorCategory.CONFIGURATION, {"action": "Run 'gemini auth login'"}
)
Verification: Run the command with --help flag to verify availability.
Error Result
@dataclass
class ErrorResult:
category: ErrorCategory
message: str
recoverable: bool
suggested_action: str
metadata: dict
Verification: Run the command with --help flag to verify availability.
Common Patterns
Authentication Errors (401/403)
- Verify credentials exist
- Check token expiration
- Validate permissions/scopes
- Suggest re-authentication
Rate Limit Errors (429)
- Extract retry-after header
- Log for quota tracking
- Implement backoff
- Consider alternative service
Timeout Errors
- Increase timeout for retries
- Break into smaller requests
- Use async patterns
- Consider different model
Context Too Large (400)
- Estimate tokens before request
- Split into multiple requests
- Reduce input content
- Use larger context model
Integration Pattern
# In your skill's frontmatter
dependencies: [leyline:error-patterns]
Verification: Run the command with --help flag to verify availability.
Detailed Resources
- Classification: See
modules/classification.mdfor error taxonomy - Recovery: See
modules/recovery-strategies.mdfor handling patterns - Agent Damage Control: See
modules/agent-damage-control.mdfor multi-agent error recovery and escalation
Exit Criteria
- Error classified correctly
- Appropriate recovery attempted
- User-actionable message provided
- Error logged for debugging
Signals
- GitHub stars
- 337
- Forks
- 34
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
error-patterns- Source
- github.com/athola/claude-night-market