Acceptance-criteria-driven development skill pack for AI coding agents — done isn't a feeling, it's a checklist.

An extension to manage acceptance criterias

Repo-local verification protocol for AI coding agents: acceptance criteria, separate verifier roles, proof artifacts, and evidence-backed done claims.

Spec-driven coding skills for AI agents: plan with acceptance criteria, self-correct from feedback, and remember reusable project knowledge.

Turn vague requirements into testable specs: BDD narratives, use cases, payload contracts, flowcharts, and dependency diagrams - Agent Skill

Simple app to practice TDD, BDD, modular design and composable storyboards

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

Verification layer for AI-assisted development. Agents don't get to self-certify — settle gates re-check declared acceptance criteria and refuse until the evidence holds. CLI · Claude Code · Codex · MCP.

A small brief before AI writes code. Make AI coding less vague and easier to continue.

Tutoring app design documents. Project for the OpenClassrooms course - Front-End Developer.

Refactoring Horiseon's website to incorporate accessibility best practice and HTML5 semantics.

Typed spec-driven development with deterministic verification — from shell commands to formal proofs

Product-facing acceptance protocol for AI-generated code. Don't trust "done". Ask for evidence.

End-to-end Business Analyst project on Superstore dataset using SQL and Excel. Includes dashboards, SQL queries, insights, recommendations, and BA documentation (BRD, FRD, User Stories).

BA portfolio project using SQL Server, Power BI, Confluence, Jira, and Draw.io to analyze Olist marketplace CX, delivery risk, RFM, and seller intervention.

This repository contains acceptance criteria, test case & bug report for a payment system.

Laravel API Toolkit is designed for exclusive use in development environments, equipping developers with everything needed to build robust, performant APIs while maintaining high code quality and adhering to best practices.

Estruturação de Critérios de Aceitação em Arquivos .feature Este exercício tem como objetivo praticar a escrita de Critérios de Aceitação utilizando a linguagem Gherkin, a partir de histórias de usuário previamente fornecidas. O foco está na organização, clareza, rastreabilidade e aplicação de boas práticas de BDD (Behavior Driven Development).

AI product and operations case study for turning business intent into agent-ready product and engineering handoffs.

Turns raw product requirements into testable acceptance criteria, coverage notes, and machine-readable contracts.