/quota-management

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
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