A structured framework for AI agents to evaluate project performance, document technical growth, and analyze problem-solving workflows.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install proj-2
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 proj-2 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 Self-Reflection & Post-Mortem?
The Self-Reflection & Post-Mortem skill is designed to facilitate a deeper understanding of the development lifecycle within the ecosystem of Openclaw Skills. It allows an AI agent or developer to systematically document the journey of a project, focusing on technical implementation, architectural planning, and the resolution of complex bugs. By synthesizing these experiences, the skill transforms raw development tasks into a structured knowledge base of professional growth.
This skill emphasizes the importance of planning and system design, helping users identify strengths and weaknesses in their current workflow. It serves as a continuous learning tool that ensures every challenge encountered becomes a documented lesson for future projects, making it an essential component for any developer looking to refine their technical expertise.
Self-Reflection & Post-Mortem Use Cases
- Documenting technical lessons learned after completing a complex feature implementation.
- Performing a root-cause analysis after resolving critical system bugs or unexpected errors.
- Tracking the evolution of programming and system architecture skills over the course of a project.
- Evaluating time management efficiency to improve future project scheduling and discipline.
How Self-Reflection & Post-Mortem Works
- The agent triggers the reflection process upon project completion or after encountering a significant technical hurdle.
- It analyzes the specific challenges faced, including the research steps taken and the debugging strategies employed.
- The skill categorizes the experience into technical skills, problem-solving abilities, and personal growth metrics.
- A structured Markdown report is generated, providing a permanent record of the learning journey to be utilized by other Openclaw Skills for future task optimization.
Self-Reflection & Post-Mortem Setup
To enable self-reflection capabilities, ensure your environment is configured to store and retrieve reflection logs.
# Create a dedicated directory for reflection logs
mkdir -p ./logs/reflections
# Initialize the documentation template
touch ./logs/reflections/SKILL_LEARNING.md
Integrate the reflection prompt into your agent's post-task routine to ensure consistent documentation of all Openclaw Skills performance metrics.
Self-Reflection & Post-Mortem Data Schema & Taxonomy
The skill organizes metadata and reflection logs using a structured taxonomy to ensure historical data is easily searchable.
| Data Point | Description |
|---|---|
| Introduction | Context of the development phase and overall project goals. |
| Learning Experience | Deep dive into system design, planning, and practical implementation. |
| Challenges | Log of technical errors, research sources, and resolution paths. |
| Skills Matrix | Inventory of developed technical, research, and time-management skills. |
| Growth Analysis | Qualitative evaluation of confidence and independent problem-solving. |
Self-Reflection & Post-Mortem Advanced Features
- Automated identification of recurring technical bottlenecks across different projects.
- Comparative analysis of system design planning versus actual implementation time.
- Support for multi-agent retrospectives to coordinate learning across an Openclaw Skills fleet.
- Strategic persistence tracking to monitor project completion rates and independent task management.
SKILL.md
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