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Bayesian Modeling and Inference with PyMC

K-Dense-AI/claude-scientific-skills

PyMC is a powerful Python library for probabilistic programming and advanced Bayesian inference. This comprehensive guide details the full workflow for building, fitting, and validating complex Bayesian models. Learn to implement hierarchical structures, perform MCMC sampling (NUTS), conduct posterior predictive checks (PPC), and effectively quantify uncertainty using industry best practices.

Quantitative Analysis Tool

quantitative-analysis

sickn33/antigravity-awesome-skills

Provides a concise quantitative analysis experience for financial or research scenarios by structuring numerical data insights and interpretations.

Explicitly Save Project Knowledge

alirezarezvani/claude-skills

A command to explicitly record critical, project-specific facts, conventions, or hard-won debugging insights into an auto-memory file. Use this when a piece of knowledge is too crucial to rely on the AI's automatic observation, ensuring the system retains key details for all future sessions in this project.

Smart Test Reporting

alirezarezvani/claude-skills

Automatically gather Playwright test outcomes, highlight failures/flakies, and deliver summaries (Markdown, Slack, TestRail, HTML) aligned with existing workflows for quick triage.

Playwright Test Review

alirezarezvani/claude-skills

Systematically audit Playwright test files against documented anti-patterns, rate their quality, and summarize findings so teams can fix flaky or under-tested scenarios before release.

State Management and Persistence Patterns

robius-state-management

sickn33/antigravity-awesome-skills

This skill provides best practices for managing application state and ensuring data persistence within large-scale applications, particularly for systems using Makepad architecture (Robrix/Moly). It details core structures like AppState, techniques for passing state through widget trees (Scope), and handling persistent data serialization (serde) across sessions, making it essential for building robust, multi-session UIs.

SciPy Scientific Library Tools

sickn33/antigravity-awesome-skills

SciPy provides open-source algorithms and utilities for scientific computing, including integration, optimization, statistics, and signal processing, enabling researchers and engineers to build reliable numerical applications.

Semgrep Rule Creator for Static Analysis

semgrep-rule-creator

sickn33/antigravity-awesome-skills

This skill provides a comprehensive guide for creating production-quality custom Semgrep rules. It teaches best practices for detecting security vulnerabilities, enforcing robust coding standards, and identifying specific bug patterns. By emphasizing a test-first approach and utilizing advanced techniques like taint mode, users can write highly accurate static analysis rules that drastically reduce false positives.

Site Architecture Strategy

site-architecture

alirezarezvani/claude-skills

Designs and audits website architecture, URL hierarchies, navigation zones, and internal linking to improve crawlability, topical authority, and SEO outcomes across existing or new projects.

Iterative Skill Improvement Methodology

sickn33/antigravity-awesome-skills

This skill provides a systematic methodology for iteratively improving complex skill documentation. By utilizing a reviewer agent, it identifies and categorizes issues (Critical, Major, Minor) in a structured loop. The process ensures that the skill meets high standards of quality, reliability, and functional completeness before deployment, moving beyond simple manual edits.

Agent Skill Security Auditor

sickn33/antigravity-awesome-skills

A comprehensive, multi-phase security audit tool designed to evaluate AI agent skills before deployment. It detects critical vulnerabilities, including prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks, ensuring the integrity and safety of your agent environment.

Skill Creation and Improvement Workflow

sickn33/antigravity-awesome-skills

A comprehensive, canonical workflow for defining, writing, and improving complex AI skills. It guides users through a structured, multi-step process, including resolving targets, synthesizing information, enforcing depth gates, authoring artifacts, optimizing descriptions, and conducting thorough evaluation and validation.

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