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AI/MLathola

quota-management

Tracks quotas, monitors thresholds, and degrades gracefully for rate-limited APIs. Use when integrating external services that impose rate or cost limits.

Stars
294
Source
athola/claude-night-market
Updated
2026-05-30
Slug
athola--claude-night-market--quota-management
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/athola/claude-night-market/HEAD/plugins/leyline/skills/quota-management/SKILL.md -o .claude/skills/quota-management.md

Drops the SKILL.md into .claude/skills/quota-management.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

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:

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