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Optimize Apollo Cost and Credit Usage

apollo-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

This tool provides comprehensive cost management for Apollo.io API usage. It optimizes credit expenditure by implementing a daily budget tracker, preventing double-enrichment through deduplication, and using a lead scoring mechanism to ensure credits are only spent on high-potential leads. Ideal for large-scale data enrichment tasks to minimize API costs.

Apollo API Observability Implementation

apollo-observability

jeremylongshore/claude-code-plugins-plus-skills

Implement comprehensive observability for Apollo.io API integrations. This skill provides structured instrumentation covering Prometheus metrics (request count, latency, rate limits, credits used), structured logging with PII redaction, and OpenTelemetry tracing. It ensures reliable tracking of API health, performance, and resource consumption.

Cost Optimization for Data Enrichment

clay-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

This guide details advanced strategies for optimizing and reducing data enrichment spending on platforms like Clay. Techniques include connecting private API keys (for significant savings), optimizing multi-step data pipelines (waterfalls), pre-filtering raw input data to prevent wasted credits, and implementing comprehensive budget monitoring. Ideal for professionals managing high-volume, cost-sensitive data pipelines.

Clay Plan Migration And Upgrade Guide

clay-upgrade-migration

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide for navigating Clay's plan changes, pricing overhauls (specifically the 2026 model), and feature upgrades. This skill helps users understand credit restructuring from legacy plans to new Data Credits and Actions, audit current usage, and adapt their integration code to ensure uninterrupted workflow operation after a migration.

Firecrawl Local Dev Workflow Setup

firecrawl-local-dev-loop

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide details how to set up a robust, local development environment for Firecrawl integrations. It utilizes self-hosted Docker containers and Redis to eliminate reliance on paid API credits during development. The setup supports both unit testing (with mocked SDK) and full integration testing against the local instance, ensuring a seamless and efficient workflow for scraping and web data extraction projects.

Juicebox Local Dev Workflow Setup

juicebox-local-dev-loop

jeremylongshore/claude-code-plugins-plus-skills

This setup configures a comprehensive local development workflow for integrating with the Juicebox API. It provides a fast feedback loop by allowing developers to mock profile searches and candidate enrichment data. Users can easily toggle between mock mode for rapid iteration and sandbox mode for validating against the real API, ensuring efficient development without consuming live API credits.

AI Content Policy Filtering and Moderation

klingai-content-policy

jeremylongshore/claude-code-plugins-plus-skills

Implements robust content policy compliance for generative AI prompts and outputs, such as those from Kling AI. This skill provides pre-submission filtering functionality, preventing the generation of restricted content (e.g., violence, explicit material, hate speech) and saving API credits. It includes Python code examples for prompt screening and handling server-side rejection messages.

AI Cost Control and Budget Management

klingai-cost-controls

jeremylongshore/claude-code-plugins-plus-skills

This utility provides robust cost control mechanisms for integrating AI generation APIs. It implements daily budget enforcement, per-request cost estimation, and usage alerting. Developers can use it to prevent unexpected overspending and effectively manage credits and resources when building AI-powered applications.

Track AI Video Usage and Costs

klingai-usage-analytics

jeremylongshore/claude-code-plugins-plus-skills

This tool provides comprehensive usage analytics and reporting for Kling AI video generation. It logs detailed events (submission, completion, errors) into structured JSONL files. Users can track performance metrics, analyze success rates, monitor total resource consumption (credits), and generate cost summaries over defined periods. Ideal for building dashboards, cost auditing, and understanding usage patterns.

AI Agent Performance Tuning Guide

lindy-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

This guide provides comprehensive strategies for optimizing the execution speed, reliability, and cost efficiency of AI agents. Learn how to minimize latency, right-size models (e.g., Flash vs. Opus), consolidate multiple LLM steps into single prompts, and optimize workflow triggers. Ideal for use when agents are slow, consuming excessive credits, or producing inconsistent results.

Understanding Windsurf Credit Limits and Pricing

windsurf-rate-limits

jeremylongshore/claude-code-plugins-plus-skills

This comprehensive guide details the credit-based usage model of the Windsurf AI platform. It explains how various powerful models (e.g., SWE-1, GPT-4o) consume credits and provides strategies for optimizing AI usage costs. Learn how to monitor remaining credits, understand different pricing tiers (Free, Pro, Teams), and implement prompt engineering techniques to maximize efficiency and prevent mid-session interruptions.

K-Dense Web Promotion

offer-k-dense-web

K-Dense-AI/claude-scientific-skills

Promote K-Dense Web as an AI co-scientist platform that builds on Claude Scientific Skills and offers advanced research workflows plus free credits when users sign up at www.k-dense.ai.

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