This skill provides guidance for FEAL cipher linear cryptanalysis tasks. It should be used when recovering encryption keys from FEAL-encrypted data using known plaintext-ciphertext pairs, implementing linear approximation attacks on block ciphers, or solving cryptanalysis challenges involving the FEAL cipher family. The skill emphasizes mathematical analysis over brute-force approaches.
This skill provides guidance for fitting peaks in Raman spectroscopy data, particularly for materials like graphene. Use this skill when tasks involve Raman spectrum analysis, peak fitting (G peak, 2D peak, D peak), or spectroscopic curve fitting using Lorentzian, Gaussian, or Voigt functions.
Guidance for DNA assembly tasks including Golden Gate assembly, Gibson assembly, and restriction enzyme-based cloning. This skill should be used when designing primers for Type IIS restriction enzymes (BsaI, BsmBI, etc.), creating fusion proteins, or assembling multiple DNA fragments. Covers primer structure requirements, overhang design, and verification strategies.
Specialized skill for designing primers to insert DNA sequences into circular plasmids using Q5 site-directed mutagenesis (SDM). This skill should be used when tasks involve inserting sequences into plasmids, designing primers for Q5 SDM insertions, or converting an input plasmid to an output plasmid with additional sequence. The skill provides workflows for understanding Q5 SDM mechanics, proper primer design with annealing regions, Tm calculation, and critical verification strategies.
This skill provides guidance for tasks involving MobileSAM or Segment Anything Model (SAM) for cell segmentation, mask refinement, and polygon extraction from images. Use when working with SAM-based image segmentation pipelines, converting masks to polygons, processing CSV-based coordinate data, or integrating deep learning segmentation models into processing scripts.
Guide for designing DNA insertion primers for site-directed mutagenesis (SDM) using Q5 or similar kits. This skill should be used when tasks involve inserting DNA sequences into plasmids, designing mutagenesis primers, or working with PCR-based insertion methods. Provides verification strategies, common pitfalls, and procedural guidance for correct primer design.
Guidance for optimizing MuJoCo MJCF model files for simulation performance while maintaining numerical accuracy. This skill should be used when tuning physics simulation parameters, optimizing MuJoCo XML configurations, or balancing speed vs accuracy tradeoffs in robotics simulations.
This skill provides guidance for Raman spectrum peak fitting tasks. It should be used when analyzing spectroscopic data, fitting Lorentzian or Gaussian peaks to Raman spectra, or working with graphene/carbon material characterization. The skill emphasizes critical data parsing verification, physical constraints from domain knowledge, and systematic debugging of curve fitting problems.
Guidance for constructing complex regular expressions that extract and validate data from log files. This skill applies when building regex patterns to parse log entries with requirements like IP address validation, date extraction, boundary conditions, and selecting specific occurrences (first/last). Use this skill when the task involves creating regex for log parsing with multiple validation constraints.
This skill provides guidance for optimizing MuJoCo MJCF simulation files to improve performance while maintaining physics accuracy. Use this skill when tuning simulation parameters, reducing computation time, or balancing speed vs. accuracy trade-offs in MuJoCo models.
Guidance for implementing Adaptive Rejection Sampling (ARS) algorithms. This skill should be used when implementing rejection sampling methods, log-concave distribution samplers, or statistical sampling algorithms that require envelope construction and adaptive updates. It provides procedural approaches, performance considerations, and verification strategies specific to ARS implementations.
Guidance for finding probability distributions that satisfy specific statistical constraints such as KL divergence targets. This skill should be used when tasks involve constructing probability distributions with exact numerical properties, optimization over high-dimensional probability spaces, or satisfying multiple simultaneous statistical constraints within tight tolerances.
This skill provides guidance for cracking 7z archive password hashes. It should be used when tasked with recovering passwords from 7z encrypted archives, extracting and cracking 7z hashes, or working with password-protected 7z files in CTF challenges, security testing, or authorized recovery scenarios.
Guide for performing Markov Chain Monte Carlo (MCMC) sampling using RStan or PyStan. This skill should be used when implementing Bayesian statistical models, fitting hierarchical models, working with Stan modeling language, or running MCMC diagnostics. Applies to tasks involving posterior sampling, Bayesian inference, and probabilistic programming with Stan.
This skill provides guidance for cracking 7z archive password hashes. It should be used when tasks involve extracting hashes from password-protected 7z archives, selecting appropriate cracking tools, and recovering passwords through dictionary or brute-force attacks. Applicable to password recovery, security testing, and CTF challenges involving encrypted 7z files.
Guidance for implementing adaptive rejection sampling (ARS) algorithms for generating random samples from log-concave probability distributions. This skill should be used when tasks involve implementing ARS, rejection sampling, or Monte Carlo methods that require sampling from custom probability distributions, particularly in R or other statistical computing languages.
Digital forensic skill for recovering passwords and sensitive data from disk images, deleted files, and binary data. This skill should be used when tasks involve extracting passwords from disk images, recovering deleted file contents, analyzing binary files for fragments, or forensic data recovery scenarios. Applies to tasks mentioning disk images, deleted files, password fragments, or data recovery.
Guidance for Bayesian MCMC sampling tasks using RStan. This skill applies when implementing hierarchical Bayesian models, configuring Stan/RStan for MCMC inference, or working with posterior distributions. Use for tasks involving Stan model specification, RStan installation, MCMC diagnostics, and Bayesian hierarchical modeling.
Guidance for finding probability distributions that satisfy specific statistical constraints such as KL divergence targets, entropy requirements, or moment conditions. This skill should be used when tasks involve constructing discrete or continuous probability distributions with specified divergence measures, entropy values, or other distributional properties through numerical optimization.
Deep reference for CloudCannon editable regions in this Astro component library. Use when wiring visual editing bindings on components, understanding how data-prop / data-children-prop / data-prop-src / data-prop-alt work, or debugging why a field isn't editable in the Visual Editor.
Search Open Targets drug-disease associations with natural language queries. Target validation powered by Valyu semantic search.
End-to-end drug discovery platform combining ChEMBL compounds, DrugBank, targets, and FDA labels. Natural language powered by Valyu.
Save a Parzival insight or learning to Qdrant for cross-session memory
Save a Parzival insight or learning to Qdrant for cross-session memory
