Quota Management

Overview

Universal patterns for tracking and enforcing resource quotas across any rate-limited service. This skill provides the foundational infrastructure that other plugins can use for consistent quota handling.

When to Use

• Building integrations with rate-limited APIs
• Need to track usage across sessions
• Want graceful degradation when limits approached
• Require cost estimation before operations

Core Concepts

Quota Thresholds

Three-tier threshold system for proactive management:

Quota Types

@dataclass
class QuotaConfig:
    requests_per_minute: int = 60
    requests_per_day: int = 1000
    tokens_per_minute: int = 100000
    tokens_per_day: int = 1000000

Quick Start

Check Quota Status

from leyline.quota_tracker import QuotaTracker

tracker = QuotaTracker(service="my-service")
status, warnings = tracker.get_quota_status()

if status == "CRITICAL":
    # Defer or use fallback
    pass

Record Usage

tracker.record_request(
    tokens=estimated_tokens,
    success=True,
    duration=elapsed_seconds
)

Estimate Before Execution

can_proceed, issues = tracker.can_handle_task(estimated_tokens)
if not can_proceed:
    print(f"Quota issues: {issues}")

Integration Pattern

Other plugins reference this skill:

# In your skill's frontmatter
dependencies: [leyline:quota-management]

Then use the shared patterns:

1. Initialize tracker for your service
2. Check quota before operations
3. Record usage after operations
4. Handle threshold warnings gracefully

Detailed Resources

• Threshold Strategies: See modules/threshold-strategies.md for degradation patterns
• Estimation Patterns: See modules/estimation-patterns.md for token/cost estimation

Exit Criteria

• Quota status checked before operation
• Usage recorded after operation
• Threshold warnings handled appropriately