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AI Agent Observability and Metrics Monitoring

lindy-observability

jeremylongshore/claude-code-plugins-plus-skills

This guide details how to implement comprehensive observability for AI agents. It covers monitoring key metrics such as task success rates, step failures, execution duration, and credit consumption. Use this when setting up performance dashboards, configuring real-time alerts (via webhooks/Prometheus), or tracking agent reliability over time.

LinkedIn Automation CLI Tool

sickn33/antigravity-awesome-skills

The LinkedIn Automation CLI Tool allows users to programmatically interact with LinkedIn content and functionality. It supports fetching detailed profiles, searching people and companies, and managing connections directly from scripts or AI agents. Ideal for building automated research, recruiting, or outreach workflows, providing structured JSON output for reliable integration into custom systems.

X/Twitter Data Scraping and Automation Suite

x-twitter-scraper

sickn33/antigravity-awesome-skills

A comprehensive toolkit designed for advanced data scraping and automation workflows on X/Twitter. Capabilities include deep tweet search, user profile analysis, bulk follower/media export, automated posting (replies, DMs), real-time account monitoring via webhooks, and integration with multiple AI agent platforms (Hermes, OpenClaw). Ideal for market research, social listening, and content automation.

Automated AI Data Scraping Agent

data-scraper-agent

affaan-m/everything-claude-code

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

Detecting DNS Exfiltration with Zeek Analysis

detecting-exfiltration-over-dns-with-zeek

mukul975/Anthropic-Cybersecurity-Skills

This skill provides a methodology to detect data exfiltration attempts hidden within DNS queries. By analyzing Zeek dns.log files, the agent computes Shannon entropy of subdomains, flags unusually long labels, and monitors unique subdomain counts per parent domain. This technique is crucial for identifying malicious tunneling tools like dnscat2 or iodine that bypass traditional security controls.

Snowflake Development Guide

snowflake-development

sickn33/antigravity-awesome-skills

Comprehensive Snowflake development assistant covering SQL best practices, dynamic tables, streams, tasks, Snowpipe, Cortex AI functions/agents, Snowpark Python, dbt integration, performance tuning, and security hardening for production data platforms.

Monte Carlo Monitor Builder

monte-carlo-monitor-creation

sickn33/antigravity-awesome-skills

Guides agents through validation, dry-run MCP tool usage, and monitors-as-code YAML generation so Monte Carlo monitors can be established via CLI or CI/CD without directly creating assets.

Push Metadata and Logs to Monte Carlo

monte-carlo-push-ingestion

sickn33/antigravity-awesome-skills

An expert agent designed to collect critical data assets—including metadata, data lineage, and query logs—from any data warehouse platform. It uses the push ingestion API to send this data directly to Monte Carlo. This method is essential for integrating data sources that cannot be reliably covered by standard pull collectors, such as custom lineage paths or historical query logs.

Autonomous Deep Research and Synthesis

rohitg00/awesome-claude-code-toolkit

An autonomous research agent that plans complex investigations using Directed Acyclic Graphs (DAGs). It executes sub-questions in parallel, performs gap analysis, and iteratively refines findings before synthesizing a comprehensive, structured report. Ideal for deep market analysis, academic literature reviews, or complex problem-solving requiring multiple data sources.

Clustering Bug Reports From Social Media

jeremylongshore/claude-code-plugins-plus-skills

This internal agent skill processes raw X/Twitter posts into structured bug candidates. It systematically performs parsing, content deduplication, PII redaction, reliability scoring, and classification. Finally, it clusters related reports using deterministic signatures, providing a highly organized output for efficient bug triage and analysis from large-scale social media streams.

Semantic Epistemic Review for Research Artifacts

ara-rigor-reviewer

Orchestra-Research/AI-Research-SKILLs

This tool performs a rigorous Level 2 semantic epistemic review of Agent-Native Research Artifacts (ARAs). It assesses six critical dimensions—including evidence relevance, falsifiability, and methodological rigor—to determine the content's intellectual soundness. It is used after initial structural validation to provide objective, constructive criticism, scoring the work from Strong Accept to Reject.

Universal Deep Research Agent Team

Imbad0202/academic-research-skills

A comprehensive, domain-agnostic 13-agent system designed for rigorous academic research on any topic. It guides users through the entire research lifecycle, supporting deep literature reviews, systematic meta-analysis, cross-source synthesis, bias assessment, and generating professional APA 7.0 reports. Ideal for academics, students, and analysts needing structured, deep insights.

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