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Log Source Onboarding for SIEM Platforms

performing-log-source-onboarding-in-siem

mukul975/Anthropic-Cybersecurity-Skills

This skill outlines the systematic process of integrating new data sources (e.g., Firewalls, EDR, Cloud, AD) into a SIEM platform. It covers planning, configuring collectors, building parsers, normalizing data fields (e.g., CIM), and validating data quality to enhance security monitoring and incident detection capabilities.

Monitoring Paste Sites for Leaked Credentials

performing-paste-site-monitoring-for-credentials

mukul975/Anthropic-Cybersecurity-Skills

This skill automates the monitoring of public paste sites (e.g., Pastebin, GitHub Gists) to detect leaked credentials, API keys, and sensitive data dumps. It employs advanced regex patterns and keyword matching to provide early warning of security breaches, crucial for incident response, vulnerability assessment, and threat intelligence gathering.

Real-Time Ransomware Encryption Detection

detecting-ransomware-encryption-behavior

mukul975/Anthropic-Cybersecurity-Skills

This system detects ransomware by combining multiple advanced techniques: real-time entropy analysis, file system I/O monitoring, and behavioral heuristics. It identifies abnormal mass file modification patterns, sudden spikes in data entropy (indicating encryption), and suspicious process activities like shadow copy deletion. Ideal for building advanced EDR detection layers to catch zero-day and unknown ransomware variants.

Comprehensive Data Quality Auditor

data-quality-auditor

alirezarezvani/claude-skills

This expert tool provides deep, systematic auditing of datasets to assess completeness, consistency, accuracy, and structural validity. It performs full data profiling, detects anomalies (outliers), analyzes missing data mechanisms (MCAR/MAR/MNAR), and calculates a Data Quality Score (DQS). Use it when validating data for model training, debugging pipelines, or establishing ongoing monitoring checks.

Operational Dashboard Builder

dashboard-builder

affaan-m/everything-claude-code

This tool guides the creation of actionable monitoring dashboards for observability platforms like Grafana and SigNoz. Instead of merely displaying raw metrics, it focuses on structuring data to answer critical operational questions: Is the system healthy? Where are the bottlenecks? What changes occurred? And what action should be taken? It transforms raw metrics into decision-making tools.

Firebase Storage in Flutter

firebase-storage

evanca/flutter-ai-rules

A practical guide for using Firebase Cloud Storage in Flutter apps. Covers setup, file upload/download, metadata management, error handling, progress monitoring, and security rules.

Manage Annotation Configs and Queues

arize-annotation

github/awesome-copilot

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

Generating Deep Links to Arize UI

github/awesome-copilot

This skill generates deep, clickable URLs to various resources within the Arize monitoring UI. It supports linking to specific traces, spans, sessions, datasets, evaluators, and annotation configurations. It is essential for sharing specific debugging artifacts or navigating directly to key data points within the MLOps platform by requiring precise resource IDs and time ranges.

Make Scenario Automation and Monitoring

make-automation

sickn33/antigravity-awesome-skills

A powerful tool utilizing Rube MCP to automate interactions with Make (formerly Integromat) scenarios. It allows users to retrieve detailed operation logs, monitor usage data, and validate critical configuration parameters such as supported languages and timezones. Ideal for building comprehensive workflow monitoring dashboards and ensuring the integrity of complex integration pipelines.

Arize LLM Judge and Monitoring

arize-evaluator

github/awesome-copilot

This skill guides users on setting up and running LLM-as-judge evaluations using Arize. It covers defining evaluators (including prompts, classification choices, and models) and executing tasks against real data spans or experiments. It supports key metrics like hallucination, faithfulness, and correctness, and facilitates continuous monitoring for comprehensive LLM performance analysis.

Datadog Automation Toolkit

datadog-automation

sickn33/antigravity-awesome-skills

Automate Datadog monitoring tasks via Rube MCP’s Composio toolkit—query metrics, search logs, manage monitors/dashboards, and create events or downtimes while respecting live tool schemas.

Automate Sentry Monitoring and Issue Management

sentry-automation

sickn33/antigravity-awesome-skills

A comprehensive automation toolkit for managing Sentry error tracking and monitoring operations. Users can programmatically investigate issues, configure project-level alert rules, manage release versions, and monitor organizational structure. Essential for DevOps and development teams needing deep integration and programmatic control over error data.

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