Antony Sure

Automate comprehensive QA verification for your projects with Ship Test.

Initialize a new Bayes Ship product project quickly and efficiently.

Ensures implementation strictly adheres to specifications, identifying missing requirements and over-building.

Configure preferences for the Bayes Ship framework with customizable settings.

Complete a feature branch with flexible merge options and automated cleanup.

Trigger a manual code review of recent changes with a two-stage process.

Context rot prevention and subagent orchestration rules. Enforces clean context windows, file-based state, and delegation patterns. Auto-invoked during any Bayes Ship execution phase.

Creates atomic execution plans with file decomposition, task sizing, model routing, TDD blocks, and wave grouping.

Stage 2 of two-stage review. Reviews code style, patterns, bugs, security, test quality. Only runs AFTER spec compliance passes.

Manage package versions and dependencies for the LangChain ecosystem in Python and TypeScript.

Create isolated git worktrees for feature implementation with a verified test baseline.

Build AI agents using LangChain's create_agent, tools, and middleware patterns.

Enforces complete output during implementation tasks to prevent lazy coding practices.

Execute plans with fresh subagents using TDD and a mandatory two-stage review process.

Establishes universal coding conventions for TypeScript, JavaScript, React, and Node.js.

UI audit and upgrade skill that identifies design issues and suggests structured fixes.

Enforces RED-GREEN-REFACTOR TDD cycle during implementation. Write the failing test first, watch it fail, write minimal code, watch it pass, commit. Code written before tests must be deleted and restarted. Use when writing any implementation code within the Bayes Ship pipeline.

4-phase root cause debugging process. Gather evidence, form hypotheses, test hypotheses, confirm root cause. Use for any bug diagnosis within the Bayes Ship pipeline. Includes defense-in-depth and condition-based-waiting techniques.

Automated security scanning against OWASP Top 10 vulnerabilities and secret detection.

Spawn parallel research subagents to investigate tech choices and libraries based on requirements.

A premium UI aesthetic designed for fintech and professional tools, emphasizing trust and quality.

Build Retrieval-Augmented Generation pipelines for effective document retrieval and context-based responses.

Automate your build process with fully autonomous or semi-autonomous modes.

Create complex, stateful AI workflows using LangGraph's StateGraph for multi-step processes.

Atomic Planning is a task decomposition methodology for Bayes Ship that streamlines project planning.

Enhance frontend design with a premium skill that ensures unique layouts, typography, and motion.

WCAG accessibility patterns: ARIA labels, keyboard navigation, screen reader support, color contrast, focus management. Use during QA phase for any product with a UI. Source: everything-claude-code.

Generate a structured PRD from discovery and research outputs with automated review.

Minimalist Skill offers a clean, editorial-style UI aesthetic for content-heavy applications.

Define system architecture based on approved PRD and research, producing comprehensive documentation.

Eval-driven development framework for AI features to ensure quality and reliability.

React and Next.js patterns for state management, component architecture, rendering, forms, and data fetching. Use when implementing frontend tasks. Source: everything-claude-code.

API design, query optimization, repository/service layer patterns for Node.js, Express, and Next.js backends. Use when implementing backend tasks. Source: everything-claude-code.

Automate deployments to Railway, Vercel, and other platforms with built-in checks.

Facilitates interactive requirements gathering through structured Q&A with users.

Bayes Ship is an end-to-end product delivery system for Claude Code, streamlining the journey from idea to deployed prototype.

Designs system architecture from PRD and research. Produces ARCHITECTURE.md, data model, API contracts, ADRs.

Automate production deployments with a comprehensive checklist and health verification.

Manage Git worktrees for isolated feature development and testing.

Patterns for building agentic systems to enhance AI-powered product features.

Writes code following TDD discipline. Receives a single task, writes failing test first, implements minimal code, reports status signal.

Ensures PRD documents are complete, clear, and free of scope creep before user review.

Verification-before-completion agent. Runs actual checks against acceptance criteria. Evidence over claims.

REST API endpoint design, request/response patterns, versioning, error handling, and authentication patterns. Use during architecture and implementation phases. Source: everything-claude-code.

Systematic bug diagnosis and fix using a structured 4-phase approach.

Implement human-in-the-loop approval flows and custom middleware with LangChain.

Consolidates research files into a unified RESEARCH.md with clear recommendations and trade-offs.

Implement persistent memory and checkpointers for LangGraph agents to enhance conversation history and session durability.

Create atomic execution plans for specific project phases with detailed task breakdowns.

Investigates a specific tech area based on project requirements. Writes findings to a research file.

Ensures comprehensive test coverage and performs AI-specific regression testing.

Automatically generates API documentation and changelogs from your codebase and commit history.

Resume from the last checkpoint after a session restart or compaction.

Extracts product requirements through structured Q&A and generates CONTEXT.md.

Display a comprehensive progress dashboard for project tracking.

Systematic 4-phase root cause analysis. Reproduce, hypothesize, test, confirm. Includes defense-in-depth considerations.

AI regression testing for model output drift, prompt sensitivity, and embedding consistency.

Evidence-based verification pattern. Never trust "it works" without running actual checks. Verify every acceptance criterion against observable behavior. Use before marking any task or phase as complete.

Implement a two-stage code review process to ensure spec compliance and code quality.