self-improvement

Log learnings, errors, and corrections to standardized markdown files.

Updated Mar 30, 2026
One-click install
npx skills add https://github.com/harkers/forge-email-server --skill self-improvement-harkers
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: self-improvement
Source: https://github.com/harkers/forge-email-server/tree/main/skills/self-improvement
Command: npx skills add https://github.com/harkers/forge-email-server --skill self-improvement-harkers

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Captures learnings, errors, and corrections to create a living knowledge base that guides improvements across tasks, tools, and workflows.

Core Features & Use Cases

  • Central logging to .learnings/ files (LEARNINGS.md, ERRORS.md, FEATURE_REQUESTS.md) for corrections, failures, and requests.
  • Automated guidance for promotion, retention, and cross-session memory through OpenClaw integration and memory files.
  • Supports optional references, assets, and scripts to automate learning workflows and extraction of durable skills.

Quick Start

Log a learning entry to .learnings/LEARNINGS.md immediately after a notable event.

Frequently Asked Questions about self-improvement

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I log errors and corrections for continuous improvement in markdown?

To log errors and corrections for continuous improvement, capture notable events by writing structured markdown entries with standardized frontmatter to centralized `.learnings/` files like `ERRORS.md` and `LEARNINGS.md` immediately after they occur.

What is the best way to retain knowledge from command failures across different sessions?

Retaining knowledge from command failures across sessions requires storing corrections in standardized markdown logs and leveraging OpenClaw hooks to promote and discover these memory artifacts in future tasks, ensuring continuous improvement.

Can I use scripts and references to automate learning workflows and feature request tracking?

Yes, you can use scripts and references to automate learning workflows and feature request tracking, extracting durable skills and organizing user requests into standardized `.learnings/` markdown logs for continuous improvement.

Do I need OpenClaw integration to organize knowledge gaps and feature requests?

You do not need OpenClaw integration to organize knowledge gaps and feature requests, as they can be captured locally in `.learnings/` markdown files, though OpenClaw provides optional automated cross-session promotion and discovery capabilities.

Why enforce structured frontmatter in SKILL.md when logging integration errors?

Enforcing structured frontmatter in SKILL.md when logging integration errors ensures standardized metadata capture, allowing automated parsing and reliable organization of learnings, corrections, and knowledge gaps across continuous improvement workflows.