---

name: quota-management description: Tracks quotas, monitors thresholds, and degrades gracefully for rate-limited APIs. Use when integrating external services that impose rate or cost limits. alwaysApply: false category: infrastructure tags:

• quota
• rate-limiting
• resource-management
• thresholds dependencies: [] tools: [] provides: infrastructure:
  • quota-tracking
  • threshold-monitoring
  • usage-estimation patterns:
  • graceful-degradation
  • quota-enforcement
  • cost-optimization usage_patterns:
• service-integration
• rate-limit-management
• resource-monitoring complexity: intermediate model_hint: standard estimated_tokens: 500 progressive_loading: true modules:
• modules/threshold-strategies.md
• modules/estimation-patterns.md

---

Quota Management

Overview

Tracks cumulative token budgets and enforces limits. For per-call logging, use usage-logging.

Patterns for tracking and enforcing resource quotas across rate-limited services. This skill provides the infrastructure that other plugins 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

When NOT To Use

• Project doesn't use the leyline infrastructure patterns
• Simple scripts without service architecture needs

Core Concepts

Quota Thresholds

Three-tier threshold system for proactive management:

Level	Usage	Action
Healthy	<80%	Proceed normally
Warning	80-95%	Alert, consider batching
Critical	>95%	Defer non-urgent, use secondary services

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 secondary service
    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