ase

About

Agentic Software Engineering (ASE) is the opinionated Open Source companion toolkit of Dr. Ralf S. Engelschall for fusing the concept of Agentic AI Coding and traditional Software Engineering in the software development tool Anthropic Claude Code — and with reduced support also in the alternative tool GitHub Copilot CLI or OpenAI Codex CLI.

ASE ships with 49 agent skills, agent hooks, agent sub-agents, an underlying Model-Context-Protocol (MCP) service and a Command-Line Interface (CLI), incorporating reasonable methodology and automation aspects, to support the recurring tasks of a Software Developer and Software Architect.

ASE is primarily motivated by the following statement of its primary author, Dr. Ralf S. Engelschall:

"Software developers in the industrial Software Engineering context, in their recurring tasks, should leverage pre-manufactured agentic AI skills to boost their daily productivity. Those skills incorporate reasonable methodology and automation aspects while keeping the developers in the driver's seat to ensure stable result quality."

Notices

[!NOTE] TERMINOLOGY: The discipline of Agentic Software Engineering in general is Software Engineering, supported by autonomous AI Agents to perform tasks across the software development lifecycle. This ASE product in particular is also agentic, but not strictly based on autonomous agents. Instead, ASE focuses on supporting the role of a Software Engineer with Agentic AI Coding Tools towards multi-step operations and a plan/task-driven approach, but still strongly focuses on Human-in-the-Loop.

[!NOTE] TOOL SUPPORT FOCUS: The primary focus of ASE is on the Agentic AI Coding tool Claude Code. The secondary focus is on the support for GitHub Copilot CLI (just set environment variable ASE_TOOL=copilot) and OpenAI Codex CLI (just set environment variable ASE_TOOL=codex). In the future, additional support could be provided also for alternative tools — if their agent harness features (especially hooks, interactive user dialog tool, etc.) realistically allow it.

Highlights

Check out the following scenarios and corresponding ASE examples to see whether ASE is right for you:

• Boosted Sessions: You want to speed up your interactive sessions and at the same time reduce costs by reducing the number of produced LLM output tokens? → /ase-meta-config set agent.persona engineer or even /ase-meta-config set agent.persona caveman

• Alternative Approach Funnel: You prefer a plan-driven approach, but the agent harness's Plan Mode is too unstructured and too direct because you want to leverage a funnel of alternative approaches first? → /ase-code-craft hello: "ase hello" CLI command which prints a nice "Hello World" in red