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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.

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.

Track ML Experiments With Trackio

hugging-face-trackio

sickn33/antigravity-awesome-skills

Trackio is a comprehensive library for logging, visualizing, and managing ML experiment metrics and alerts. It allows developers to use a Python API to log metrics and set diagnostic alerts (INFO/WARN/ERROR) during training. Furthermore, a dedicated CLI enables metric retrieval and dashboard viewing, syncing data to Hugging Face Spaces for persistent, remote monitoring, making it ideal for autonomous ML agent workflows.

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.

Deep Academic Research Agent Team

Imbad0202/academic-research-skills

This universal 13-agent pipeline provides rigorous, deep academic research on any topic. It guides users through the entire research lifecycle, from formulating precise research questions in Socratic mode, to conducting systematic literature reviews, performing meta-analyses, and compiling final APA 7.0 reports. Ideal for students, researchers, and analysts requiring comprehensive, structured academic insights.

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