AgentSkillsCN

error-patterns

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SKILL.md
--- frontmatter
name: error-patterns
description: |
  Standardized error handling patterns with classification, recovery, and logging strategies.

  error handling, error recovery, graceful degradation, resilience
  Use when: implementing error handling in production plugins
category: infrastructure
tags: [errors, error-handling, recovery, resilience, debugging]
dependencies: [usage-logging]
provides:
  infrastructure: [error-handling, error-classification, recovery]
  patterns: [graceful-degradation, error-logging, debugging]
usage_patterns:
  - error-handling
  - resilience-patterns
  - debugging-workflows
complexity: beginner
estimated_tokens: 450
progressive_loading: true
modules:
  - modules/classification.md
  - modules/recovery-strategies.md
version: 1.4.0

Table of Contents

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

LevelActionExample
CriticalHalt, alertAuth failure, service down
ErrorRetry or secondary strategyRate limit, timeout
WarningLog, continuePartial results, deprecation
InfoLog onlyNon-blocking issues

By Recoverability

python
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

python
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

python
@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

yaml
# 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.md for error taxonomy
  • Recovery: See modules/recovery-strategies.md for handling patterns

Exit Criteria

  • Error classified correctly
  • Appropriate recovery attempted
  • User-actionable message provided
  • Error logged for debugging

Troubleshooting

Common Issues

Command not found Ensure all dependencies are installed and in PATH

Permission errors Check file permissions and run with appropriate privileges

Unexpected behavior Enable verbose logging with --verbose flag