Skill UI

Prepares Claude with an ultra-granular, line-by-line code-analysis mode that maps invariants, assumptions, and flows before any vulnerability hunting, keeping context stable and reducing hallucinations during audits.

Prepares Claude with an ultra-granular, line-by-line code-analysis mode that maps invariants, assumptions, and flows before any vulnerability hunting, keeping context stable and reducing hallucinations during audits.

Ports an existing Semgrep rule into each requested language by running applicability analysis, test-first creation, AST-informed rule translation, and validation so that every target-language variant has its own rule+test directory.

Performs pattern-driven searches for similar vulnerabilities across repositories after a known issue is found, guiding analysts through precise generalization, triage, and tool choices (ripgrep, Semgrep, CodeQL) to audit and prioritize true positives.

Pysam offers Python bindings to htslib for reading and writing SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, enabling coverage stats, pileup analysis, variant queries, and seamless integration into NGS pipelines.

Query the JASPAR REST API and Python helpers to retrieve TF binding profiles, convert PFMs to PWMs, and scan DNA sequences for high-confidence motifs, enabling regulatory variant interpretation, ChIP/ATAC analysis, and TF network construction.

This skill provides a structured workflow for porting existing Semgrep security rules to multiple target languages. It guides users through applicability analysis, test-first rule creation, and validation for each language variant, ensuring consistent and accurate security coverage across polyglot codebases.

A rigorous, multi-phase auditing skill designed for blockchain protocols. It verifies whether the implemented smart contract code strictly adheres to the detailed specifications provided in whitepapers, design documents, or technical specifications. It performs exhaustive, line-by-line semantic analysis to identify gaps, inconsistencies, and deviations across logic, invariants, and security guarantees, making it essential for formal compliance checking in decentralized systems.

A systematic skill for identifying similar vulnerabilities and bugs across large, complex codebases. It guides the user through generalizing initial bug patterns using techniques like CodeQL and Semgrep, ensuring comprehensive security audits beyond the initially discovered flaw. Ideal for advanced security research and robust code auditing.

Rigorously dissects code and architecture through advanced mathematics—graph theory, category theory, stochastic systems, information theory, and formal invariants—to uncover hidden structure and optimize performance.

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.

This skill automates the nf-core/pacsomatic pipeline for matched tumor-normal variant calling from BAM files. It handles input validation, samplesheet generation, dry-run checks, and submission to schedulers like Slurm or LSF. Ideal for reproducible bioinformatics analysis execution and troubleshooting pipeline failures.