Skill UI

Workflow for parsing SillyTavern-compatible character cards and world info from PNG/WebP/JSON files using a dedicated Node.js parser, with clear steps for copying presets, installing deps, running the extractor, and verifying results.

Datamol wraps RDKit with Pythonic APIs tailored for drug discovery, offering SMILES/SELFIES/InChI parsing, standardization, descriptor and fingerprint calculation, clustering, 3D conformer workflows, and parallel/cloud-aware batch I/O while returning native rdkit.Chem.Mol objects.

RDKit delivers a Python-based cheminformatics toolkit for parsing SMILES/SDF, computing descriptors, generating 2D/3D coordinates, fingerprinting, searching substructures, managing reactions, and visualizing molecules, ideal for drug discovery and computational chemistry workflows.

This skill provides deep technical expertise regarding the DWARF debugging format (v3-v5) and the DWARF standard. It assists in analyzing, parsing, verifying, and generating debug information from compiled binaries. Use cases include answering questions about the DWARF specification, writing code that interacts with DWARF data, and utilizing tools like `dwarfdump` or `readelf` for structural validation and quality metric extraction.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

A comprehensive guide and workflow for digital forensics investigators to analyze raw email headers. This tool helps trace the true origin of suspicious emails, verify sender authenticity, and detect advanced spoofing techniques by validating crucial protocols like SPF, DKIM, and DMARC. It covers everything from header parsing to domain infrastructure analysis and IP reputation checks.

This skill details the forensic analysis of Windows LNK shortcut files and Jump Lists. It enables investigators to reconstruct user activity, track file access, and determine program execution history by parsing critical metadata like timestamps, paths, and system identifiers, even when the original artifacts are deleted.

This guide details advanced digital forensics techniques for recovering deleted file metadata and content from NTFS volumes. It focuses on analyzing the Master File Table (MFT), USN Journals, and $LogFile transaction records. Techniques include parsing MFT slack space and utilizing specialized tools like MFTECmd to reconstruct file system timelines and identify deleted evidence remnants.

This skill guides users through parsing Windows Prefetch files (.pf) to establish a comprehensive program execution history. It extracts critical forensic data such as run counts, timestamps (up to 8 events), and referenced files. This is essential for incident response, malware investigation, and building a reliable timeline of activity on a compromised system.

This skill automates the process of parsing Cyber Threat Intelligence (CTI) reports to extract adversary behaviors. It maps these behaviors to MITRE ATT&CK techniques and structures them as STIX 2.1 Attack Pattern objects. The resulting library supports detection engineering by generating rule templates (Sigma, YARA) for proactive defense and threat-informed security control implementation.

A comprehensive guide for authorized penetration testing on detecting and exploiting HTTP Request Smuggling vulnerabilities. It details analyzing discrepancies between Content-Length and Transfer-Encoding header parsing in multi-tier architectures (e.g., CDN, reverse proxy, load balancers). Learn techniques to bypass access controls, capture subsequent user requests, and escalate attacks in a controlled environment.

A comprehensive workflow for extracting, parsing, and analyzing Windows Event Logs (EVTX). It guides security professionals in using advanced tools like Chainsaw and Hayabusa, combined with Sigma rules, to detect critical security incidents such as lateral movement, privilege escalation, and persistence mechanisms during incident response and digital forensic investigations.