Apollo Mode transforms AI agents into disciplined engineers by enforcing a strict specification, planning, and verification lifecycle for coding tasks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install apollo-mode
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install apollo-mode using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Apollo Mode: Structured Engineering Workflow?
Apollo Mode, often referred to as sysflow, is a professional-grade engineering protocol designed for AI coding agents. It moves beyond simple prompt-and-response patterns to establish a rigorous, step-by-step development process. By integrating this mode via Openclaw Skills, developers ensure their AI assistants act as reliable engineers who prioritize architectural clarity, task decomposition, and systematic verification over hasty code generation.
This skill is particularly valuable for teams and individual developers who need to maintain high code quality standards. It forces the AI to think through constraints, identify potential risks, and follow a logical path from specification to final acceptance, effectively reducing bugs and architectural debt in complex projects.
Apollo Mode: Structured Engineering Workflow Use Cases
- Managing large-scale refactoring projects that require a clear implementation plan.
- Implementing mission-critical features where a risk review and rollback strategy are essential.
- Standardizing the AI workflow for a team to ensure consistent documentation and testing practices.
- Debugging complex system-level issues that involve multiple dependencies and state assumptions.
How Apollo Mode: Structured Engineering Workflow Works
- Activation: The user enables the protocol using commands like sysflow on or enable sysflow.
- State Management: The skill writes the active status to a persistent state file at memory/sysflow-mode.md to maintain context.
- Specification: For any coding request, the AI first produces a short, chunked specification for user review.
- Planning: The AI generates a detailed implementation plan consisting of small, verifiable tasks.
- Risk Assessment: A mandatory mini-review is conducted to identify potential production failures and regression signals.
- Execution: The AI executes the plan task-by-task, ideally using a test-first approach for high-risk changes.
- Verification: Every change is verified against acceptance criteria before the task is marked as complete.
Apollo Mode: Structured Engineering Workflow Setup
To deploy Apollo Mode within your project, you need to set up the appropriate memory tracking file required by Openclaw Skills. Run the following commands in your project root:
mkdir -p memory
touch memory/sysflow-mode.md
Once the state file is initialized, you can control the workflow directly through chat commands such as sysflow on or sysflow status to verify the current engineering mode.
Apollo Mode: Structured Engineering Workflow Data Schema & Taxonomy
The skill utilizes a structured Markdown file to track the engineering state and ensure persistence across agent restarts.
| Property | Type | Description |
|---|---|---|
| enabled | Boolean | Indicates if the structured engineering workflow is currently active. |
| updatedAt | ISO8601 | The timestamp of the last mode change. |
| notes | String | Optional context or metadata regarding the current session. |
The file is stored at memory/sysflow-mode.md to ensure the AI agent can access its state via standard file system tools.
Apollo Mode: Structured Engineering Workflow Advanced Features
- Multi-language command support allowing activation through both English and Russian phrases.
- Built-in risk review module that forces the AI to evaluate production impact and rollback procedures.
- Adaptive workflow guardrails that skip heavy processes for non-coding tasks or explicit speed requests.
- Reference integration that allows the AI to pull standard templates from a references folder for specs and plans.
SKILL.md
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