# Add: A State Machine-Based Agent-Driven Development Workflow System

> A set of personal pluggable agent skills that manages software development work through epic/story lifecycle management, solves long-session context drift issues, and supports both Claude Code and Codex platforms.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-23T08:45:15.000Z
- 最近活动: 2026-04-23T08:54:57.169Z
- 热度: 159.8
- 关键词: 智能体开发, Claude Code, Codex, 工作流, 状态机, TDD, 技能系统, 项目管理
- 页面链接: https://www.zingnex.cn/en/forum/thread/add
- Canonical: https://www.zingnex.cn/forum/thread/add
- Markdown 来源: floors_fallback

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## [Introduction] Add: Core Introduction to the State Machine-Based Agent-Driven Development Workflow System

Add is a set of personal pluggable agent skills designed specifically for managing the software development lifecycle. Its core innovation lies in using a state machine model to organize workflows—each state transition corresponds to a new session, solving the context drift problem in long-term agent conversations. Work states are stored in the MASTER.md tracker and structured story files instead of conversation history, supporting both Claude Code and Codex platforms.

## [Background] Context Drift Issue in Long Agent Conversations

The core problem Add system addresses is context drift in long agent conversations: when the context window is full, the model tends to generate hallucinated file paths, lose early instructions, and a single wrong decision cascades and amplifies due to the lack of a clean state reset.

## [Methodology] State Machine Workflow Design

Add defines a clear state lifecycle; each story goes through a complete process from planning to completion: create an epic via `/epic-plan` to generate MASTER.md, plan pending stories with `/epic-story-plan`, claim and implement using TDD via `/epic-story-claim`, resume interrupted work with `/epic-story-resume`, and finally review the implementation with `/epic-story-review`. The design principles are: each command does one thing, each session executes one command, and review and coding sessions are separated to avoid bias.

## [Methodology] Institutionalization of TDD and Session Handover Mechanism

Add elevates TDD to a planning-phase constraint: `/epic-story-plan` requires providing a validation proof matrix, mapping acceptance criteria to test seams to ensure a clear testing strategy before coding. The session handover mechanism records changes, remaining work, and next steps by writing a 'Session Handover' section; knowledge retention is achieved via `/memorize` to reflect on friction points and suggest document patches, and `/epic-squash` merges completed specifications into CONTRACT.md to prevent repeated learning.

## [Technical Details] Dual-Platform Support and Installation Mechanism

Add supports both Claude Code and Codex platforms, offering two installation paths: installation via the Claude Code plugin market, or installation via a custom shell script (supports user-level/project-level scopes, implemented via symbolic links; updates only require `git pull`, and script script idempotency prevents overwriting non-symbolic links).

## [Features] Overview of Command System

Add includes 10 core workflow commands (such as `/epic-plan` for creating epics, `/epic-story-claim` for claiming stories, `/epic-story-review` for reviewing implementations, etc.) and 2 tool commands: `/grillme` for continuous questioning in planning/design to reach consensus, and `/memorize` for reflecting on session friction and suggesting document improvements. All commands share the state lifecycle and coordinated file conventions.

## [Application Scenarios] Applicable Scenarios and Practical Value

Add is suitable for complex long-term projects or multi-developer collaboration scenarios, solving agent conversation limitations through externalized states. For individual developers: the structured work approach maintains focus and reduces context switching costs; for teams: it standardizes collaboration language and processes, lowering communication overhead. It also demonstrates a new collaboration paradigm: breaking down into multiple short, focused sessions to leverage AI capabilities while avoiding their limitations.

## [Conclusion] Core Insights and Implications

The core insight of the Add project is: the real state should be stored in the file system而非对话历史. The state machine workflow built on this not only solves the context drift problem but also provides a new way of thinking for collaborating with AI. For other developers, Add provides a reference implementation, and its session handover and knowledge retention processes can be adapted to other workflows and toolchains.