shrek-abaper

Sap Transport Gate — AI skill for Claude Code

AI community

AI-powered release gate for SAP Transport Requests.

How to install Sap Transport Gate

This entry records only its repository, not the path inside it, so there is no exact command to give. Open shrek-abaper/sap-transport-gate and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Sap Transport Gate does

AI-powered release gate for SAP Transport Requests. CLI collects evidence from ADT; SKILL guides LLMs to review code, config, interfaces, and release risk — online or offline.

Alternatives in AI

  • Claude Hub — by Claude Did This - A webhook service that connects Claude Code to GitHub repositories, enabling AI-powered c 393 ★
  • Claude Skills Governance Risk And Compliance — Claude Skills for Governance, Risk & Compliance (GRC): Expert-level compliance guidance for ISO 27001, SOC 2 340 ★
  • SAP Skills - Project Context — Repository: https://github.com/secondsky/sap-skills Purpose: Production-ready skills for SAP development and A 207 ★

README

sap-transport-gate

[English](README.md) | [中文](README.zh-CN.md)

[!IMPORTANT] **This repository has been archived and is no longer updated.** `sap-transport-gate` is now maintained exclusively in the [sap-engineering-skill](https://github.com/shrek-abaper/sap-engineering-skill) monorepo at [`skills/sap-transport-gate`](https://github.com/shrek-abaper/sap-engineering-skill/tree/main/skills/sap-transport-gate). Please go there for the latest version, issues, and improvements.

AI-assisted pre-release gate review for SAP Transport Requests.

An AI agent skill that performs structured, evidence-driven release readiness assessment for SAP Transport Requests. Produces an auditable `GO / CONDITIONAL_GO / NO_GO / NEED_MORE_EVIDENCE` decision and a formal Release Readiness Report.


What It Does

`sap-transport-gate` guides an AI agent through a structured review workflow:

  1. Extract TR ID — Detect Transport Request ID from user input (pattern: uppercase letters + K + 6 digits, e.g., DEVK900123); ask if not found
  2. Identify Review Mode — Offline Package, Offline Local, or Online Transport; verify SAP credentials for Online mode
  3. Select Review Scope — User confirms: (A) Code Quality only or (B) Functional + Code Quality (spec required for B)
  4. Evidence Intake — Inventory all provided materials; flag gaps
  5. Evidence Level — HIGH / MEDIUM / LOW / UNKNOWN based on completeness
  6. Multi-Dimension Review — 10 dimensions covering the full release risk surface
  7. Finding Classification — Structured findings with severity, confidence, evidence, and recommendation
  8. Release Decision — Evidence-based GO / CONDITIONAL_GO / NO_GO / NEED_MORE_EVIDENCE
  9. Report Generation — Markdown Release Readiness Report + JSON summary

Core Principles

Principle Rule
Evidence-first AI never invents conclusions from insufficient evidence. Every finding must trace to real code, metadata, or material. Eve