
from opencode-skills-collection23
Practical guidance and commands for acquiring, analyzing, and extracting artifacts from memory dumps using tools like Volatility3 and common acquisition methods
Provides a comprehensive memory forensics playbook: acquisition steps for live systems and VMs, Volatility 3 usage and essential plugins (process, network, DLL analysis), detection patterns (injection, rootkits), YARA integration, and analysis workflows for malware and incident response. Includes best practices for acquisition, integrity verification, and documentation.
Use when performing memory acquisition or analysis during incident response, malware analysis, or forensic investigations. Suitable for analysts needing concrete commands, Volatility plugin examples, and stepwise workflows from acquisition to reporting. Not for unrelated tasks.
Agents that can run or orchestrate forensic tooling and present command outputs (e.g., Copilot-style agents, Claude Code, or custom forensic automation integrations).
A comprehensive memory forensics reference skill covering acquisition, Volatility3 analysis, malware detection workflows, YARA rules, and best practices. No scripts included — purely informational. SKILL.md references an implementation-playbook.md resource that was not bundled with the skill, reducing practical usability. Trigger conditions are overly broad.
Well-written reference material for memory forensics practitioners. Covers Windows, Linux, and macOS acquisition and analysis. Includes useful YARA rule examples and detection patterns. Main issues: (1) no bundled scripts despite referencing an implementation playbook, (2) vague trigger conditions, (3) monolithic structure with no separation into references/ or scripts/ directories. Not malicious — purely educational/reference content with no security concerns.
Python Performance Optimization
Profile, analyze, and optimize Python applications for CPU and memory efficiency using profiling tools and performance best practices.
API Security Testing Workflow
Structured workflow for testing REST and GraphQL API security: auth, authorization, rate limiting, input validation and error handling.
Azure AI Projects SDK (TypeScript)
TypeScript SDK and examples for managing Azure AI Projects: agents, connections, deployments, datasets, indexes, and evaluations.
Testing Patterns & Utilities
Guidelines and utilities for TDD, factory-based test data, mocking strategies, and testing patterns for React/TypeScript projects.
Skill Optimizer
Diagnose and optimize Agent Skills (SKILL.md) using session transcripts and static analysis to improve triggers, workflows, and token efficiency.
Reverse Engineer
Guided methodology and best practices for binary reverse engineering, covering static and dynamic analysis workflows and common tooling.