554 skills · sorted by relevance
Study and apply statistics, probability, and linear algebra through Python examples. Calculate summary statistics, compare groups, analyze A/B tests, and build regression models while checking assumptions and considering the size of observed differences.
Organize code and data projects into clear folders with documented workflows, data fields, dependencies, and changes. The skill guides new machine learning and data processing scripts, while preserving existing project structure during modifications.
Get guidance on fine-tuning language models with Unsloth, including LoRA and QLoRA methods for training with fewer resources. The skill points to documentation for understanding APIs, implementing training code, debugging problems, and exploring speed and memory optimizations.
Analyze tabular datasets too large to fit in memory using Vaex. Filter rows, calculate statistics, visualize distributions, convert file formats, and prepare machine learning workflows with operations that defer computation until results are needed.
Build PyTorch machine learning workflows for molecules, proteins, and biomedical relationships. Get guidance on datasets, model selection, training, and evaluation for property prediction, protein modeling, molecule generation, and planning synthesis routes from target molecules.
Build reinforcement learning experiments, where agents learn actions from rewards, using Stable Baselines3. Get guidance on choosing algorithms, creating Gymnasium environments, training and evaluating agents, monitoring progress, and saving models for later use.
Deploy apps and websites to Vercel and get a URL to share. The workflow defaults to preview deployments, supports production when explicitly requested, and includes an alternative deployment script when CLI credentials are unavailable.
Turn a feature specification into a technical implementation plan. Organizes technology choices, research decisions, data models, and interface agreements into project files, while checking that the design follows the project's documented principles.
Turn implementation plans and specifications into an ordered tasks.md checklist. Organize work around user stories, meaning goals expressed from a user's perspective, with file paths, dependencies, parallel work opportunities, and independent verification criteria.
Create or update a project's governing development principles, covering code quality, testing, and architectural constraints. Maintain the constitution document, record version changes, and align related planning, specification, and task templates with the revised rules.
Analyze complex tasks before implementation through four structured phases. Clarify the problem, examine dependencies and impacts, challenge assumptions, and compare alternatives to produce a decision rationale, explicit uncertainties, and actionable recommendations.
Use UMAP to reduce data with many features into fewer dimensions for plotting or further analysis. The skill guides parameter choices, preprocessing for clustering, label-guided projections, and transforming new data with an already trained model.
Plan and audit preprocessing for grouped time-series data, such as matches or patient records. Check missing-value handling, scaling scope, feature meaning, and data leakage, where information unavailable at prediction time enters model inputs.
Design and improve prompts and structured responses for AI applications. The skill also guides evaluation, retrieval augmented generation, which uses retrieved material to inform answers, and agent architecture, with references and scripts for production workflows.
Process mass spectrometry data in Python with PyOpenMS. Read common file formats, smooth and normalize signals, detect peaks, align samples, and process peptide identification results for protein and metabolite quantification workflows.
Build searches that find documents by meaning and support recommendation features using vector databases. Includes implementation patterns for storing and retrieving vectors, combining meaning with keyword matches, and tuning search speed and result quality.
Diagnose file write failures by checking permissions, disk space, paths, and file locks. Get corrective steps before retrying, or check conditions before important writes to catch problems such as missing folders and read-only files.
Manage Zotero reference libraries through Python: search, create, update, and delete records, organize collections and tags, upload PDF attachments, and export citation data for research workflows.
Explore research ideas through conversation, question existing assumptions, and connect methods across disciplines. The skill helps identify research gaps, compare ways to combine papers, and summarize promising directions with practical next steps.
Create scientific diagrams from written descriptions using Nano Banana Pro. Gemini 3 Pro reviews accuracy, labels, and layout, triggering regeneration when scores fall below the chosen document threshold, up to the iteration limit.
Draft and revise scientific manuscript prose from research notes and results. Organize sections, write abstracts and figure captions, integrate citations, and refine terminology and clarity while following study reporting guidelines and journal requirements.
Use RDKit in Python to read molecular structures, calculate properties such as molecular weight, find similar compounds or specific structural features, and generate molecular drawings and 3D coordinates for chemistry research.
Plan experiments, analyze data, and build and evaluate predictive models. The skill also covers explaining findings to stakeholders and designing production workflows for model deployment, monitoring, and retraining to support business decisions.
Bridge `/speckit.*` commands to `/vibe` execution guidance in Codex. A PowerShell router preserves the familiar command model and leaves official spec-kit prompts unchanged, helping carry existing workflows into `/vibe-first` execution.