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quota-management

// Quota tracking, threshold monitoring, and graceful degradation for rate-limited API services. quota, rate limiting, usage limits, thresholds.

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stars:201
forks:38
updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namequota-management
descriptionQuota tracking, threshold monitoring, graceful degradation for rate-limited APIs.
alwaysApplyfalse
categoryinfrastructure
tagsquota,rate-limiting,resource-management,cost-tracking,thresholds
dependencies
tools
provides[object Object]
usage_patternsservice-integration,rate-limit-management,cost-tracking,resource-monitoring
complexityintermediate
model_hintstandard
estimated_tokens500
progressive_loadingtrue
modulesmodules/threshold-strategies.md,modules/estimation-patterns.md

Table of Contents

Quota Management

Overview

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:

LevelUsageAction
Healthy<80%Proceed normally
Warning80-95%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