# Summoner: A Makefile-like Orchestration Framework for AI Agent Workflows

> Summoner is an AI Agent orchestration framework that adds a process layer to AI coding workflows via checkpoint mechanisms, post-task reviews, and memory chain features, addressing issues like agents skipping diagnosis, forgetting reviews, and repeating mistakes.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-06-09T10:44:24.000Z
- 最近活动: 2026-06-09T10:54:01.743Z
- 热度: 161.8
- 关键词: AI Agent, workflow orchestration, Claude Code, checkpoint, post-game review, memory chain, Makefile, bug fix, code review
- 页面链接: https://www.zingnex.cn/en/forum/thread/summoner-ai-agentmakefile
- Canonical: https://www.zingnex.cn/forum/thread/summoner-ai-agentmakefile
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Summoner: A Makefile-like Orchestration Framework for AI Agent Workflows

Summoner is an AI Agent orchestration framework that adds a process layer to AI coding workflows via checkpoint mechanisms, post-task reviews, and memory chain features, addressing issues like agents skipping diagnosis, forgetting reviews, and repeating mistakes.

## Original Author & Source

- **Original Author/Maintainer**: johnson-xue
- **Source Platform**: GitHub
- **Original Title**: summoner
- **Original Link**: <https://github.com/johnson-xue/summoner>
- **Publication Date**: June 9, 2026

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## Background: Pain Points of AI Coding Agents

Current AI coding agents (e.g., Claude Code, Cursor, Copilot) commonly face three core issues in practical use: **skipping diagnosis**, **forgetting reviews**, and **repeating mistakes**. When agents encounter errors, they often try to fix them directly without in-depth analysis of the root cause; after fixing, they rarely conduct systematic code reviews; and the same error patterns recur across different sessions.

Summoner's design philosophy targets these pain points—it is not a tool to replace existing agents, but rather adds a **process layer** to AI workflows. Through structured phase management and memory mechanisms, it makes agents' work more reliable and traceable.

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## Project Overview: What is Summoner

Summoner positions itself as the "Makefile for AI workflows". Just as Makefile defines the goals and dependencies of software building, Summoner defines the phases and flow rules of AI tasks. Its core features include:

- **Checkpoint Mechanism**: Pauses at key nodes to allow human intervention in decision-making
- **Post-Game Review**: Structured review after task completion, automatically recorded to SQLite
- **Memory Chain**: Automatically invokes historical repair patterns to avoid repeating mistakes
- **Cross-Platform Support**: Claude Code, Gemini CLI, OpenCode, Cursor/Windsurf/Copilot/Aider, etc.

The project uses the MIT license, with a code size of only about 7.5MB (63 files, 19 core files, compiled hooks), and zero external dependencies (only requires Go + SQLite3).

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## Core Commands & Workflows

Summoner provides five main commands covering full scenarios from bug fixing to feature development:

## `/summoner:fix` — Bug Fixing Workflow

This is the most commonly used command, executing a complete five-phase repair process:

1. **Phase 0 - Memory**: Automatically retrieves historical bug patterns
2. **Phase 1 - Diagnosis**: Root cause analysis (follows the "iron rule": never skip)
   - A checkpoint is triggered at this phase; users can choose: continue/skip/retry/stop
3. **Phase 2 - Reproduce**: Prove-It test (configuration fixes are automatically skipped)
4. **Phase 3 - Fix**: Apply the repair solution
5. **Phase 4 - Verify**: Run the test suite
6. **Phase 5 - Review**: Code review
   - Post-game review: 5 types of questionnaires, automatically recorded to SQLite

## `/summoner:new` — Feature Development Workflow

A complete new feature development process: Define → Plan → Implement → Test → Review.

## `/summoner:ship` — Pre-Release Check

Fan-out review by 1-3 reviewers → Merge decision → Go/No-Go judgment.