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Analyzing Kubernetes Audit Logs for Threats

analyzing-kubernetes-audit-logs

mukul975/Anthropic-Cybersecurity-Skills

This tool parses Kubernetes API server audit logs (JSON lines) to detect critical security events. It specifically targets unauthorized access, secret enumeration, RBAC escalation, privileged pod creation, and shell access (exec/attach). Use it for incident response, threat hunting, or building SIEM detection rules.

Collaborative Forensic Timeline Analysis Tool

building-incident-timeline-with-timesketch

mukul975/Anthropic-Cybersecurity-Skills

Timesketch is a collaborative, open-source platform for security teams to analyze and reconstruct complex forensic timelines. It ingests and normalizes multi-source security data (logs, artifacts) using methods like Plaso, CSV, and JSONL. Users can visualize event chronology, track attack chains, and utilize advanced built-in analyzers (e.g., Sigma, Chain of Events) for comprehensive incident investigation and documentation.

Monitor Machine Learning Experiment Results

monitor-experiment

wanshuiyin/Auto-claude-code-research-in-sleep

Provides a detailed, multi-platform workflow to monitor long-running computational experiments. It checks the status of jobs across various environments (SSH, vast.ai, Modal), collects screen logs, fetches structured JSON results, and pulls detailed training metrics (loss curves, accuracy) from Weights & Biases (W&B). Essential for MLOps and automated result review.

Generate Publication Figures and Tables

wanshuiyin/Auto-claude-code-research-in-sleep

Automates the generation of high-quality, publication-ready figures and comparison tables from raw experimental data (JSON, CSV). This skill is essential for academic writing workflows, handling various plot types including line graphs, bar charts, scatter plots, and heatmaps, ensuring consistency with professional style guides like LaTeX and specific DPI requirements.

Forensic Timeline Reconstruction with Plaso

performing-timeline-reconstruction-with-plaso

mukul975/Anthropic-Cybersecurity-Skills

This guide demonstrates how to build comprehensive forensic super-timelines using Plaso (log2timeline) to correlate events across diverse sources. It covers the entire workflow, from processing disk images and various logs (MFT, registry, browser history) to generating standardized CSV, JSONL exports, and visualizing the results in tools like Timesketch for deep investigative analysis.

Structured X/Twitter Post Reader

sickn33/antigravity-awesome-skills

ADHX provides a dedicated API to fetch X/Twitter posts as clean, structured JSON. It extracts comprehensive data, including author profiles, engagement metrics (likes, retweets), and full article content for long-form posts. This method is vastly superior to traditional scraping techniques, making it ideal for LLM analysis, summarization, and structured data workflows.

Data Analysis Assistant

bytedance/deer-flow

Analyzes Excel and CSV uploads with DuckDB, inspecting schemas, running SQL, summarizing statistics, and exporting results so users can explore structured data efficiently.

Shuffle JSON Data with Validation

shuffle-json-data

github/awesome-copilot

This skill safely randomizes the order of repetitive JSON objects within an array without corrupting the data or breaking the JSON syntax. It acts as a data engineer, rigorously validating the input schema (checking for property consistency and lack of nesting) before performing the shuffle. It ensures data integrity is maintained while reordering records, making it ideal for testing, simulation, or data preparation workflows.

Arize Dataset Management and Query

github/awesome-copilot

This skill provides comprehensive commands for creating, managing, versioning, and querying structured datasets within the Arize platform. It covers dataset CRUD operations, appending examples, and exporting data in various formats (JSON, CSV, Parquet) using the `ax` CLI. Ideal for preparing test data, generating evaluation examples, or retrieving golden datasets for LLM development and model testing.

Manage Research Projects and Papers

K-Dense-AI/scientific-agent-skills

The Paperzilla skill provides direct command-line access to interact with Paperzilla data. Users can fetch the latest research recommendations, summarize canonical papers in markdown format, view project feeds, leave feedback, and export data in various formats (JSON, Atom). It is essential for researchers needing structured insights into academic projects and literature.

Bounded Exploratory Data Analysis Tool

exploratory-data-analysis

K-Dense-AI/scientific-agent-skills

This skill provides bounded, local exploratory data analysis for diverse scientific data files, including CSV, JSON, HDF5, and image metadata. It rigorously audits data structure, detects missing values, and identifies outliers in a secure, sandboxed environment. It is designed exclusively for pre-modeling data integrity checks and must not be used to infer scientific meaning or make causal claims.

NetworkX: Analyzing Complex Graphs

K-Dense-AI/scientific-agent-skills

NetworkX is a powerful Python library used for generating, manipulating, and analyzing complex networks and graphs. It provides comprehensive tools for running essential graph algorithms (e.g., shortest paths, centrality, community detection), modeling diverse structures (social, biological, transportation), and handling various data formats (GraphML, JSON, Pandas). Ideal for system modeling and scientific research.

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