omk-self-reflect

Promote recurring episodes from episodes.md into rules.md after user approval.

103|15|Updated Feb 6, 2026
One-click install
npx skills add https://github.com/KaimingWan/oh-my-kiro --skill omk-self-reflect
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: omk-self-reflect
Source: https://github.com/KaimingWan/oh-my-kiro/tree/main/skills/omk-self-reflect
Command: npx skills add https://github.com/KaimingWan/oh-my-kiro --skill omk-self-reflect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Agent self-learning and rule creation for recurring issues, enabling automated consolidation of recurring mistakes into durable, reusable rules and reducing drift.

Core Features & Use Cases

  • Promotion execution: read episodes.md, distill into concise rules, and write to rules.md when approved.
  • Complex insight capture: convert difficult corrections into structured knowledge via episodes.md and rules.
  • Safe, guarded automation: marks promoted episodes and integrates with the known workflow for enforcing rules.
  • Sync targets and governance: aligns with top-level instruction files and protected flows.

Quick Start

Promote a recurring episode to a rule after user approval.

Frequently Asked Questions about omk-self-reflect

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

FAQPage Schema
How do I automate agent self-learning from recurring mistakes?

Automate agent self-learning by capturing recurring mistakes as episodes, distilling them into formal rules, and writing to rules.md. This reduces agent drift by converting repeated corrections into durable, reusable knowledge after user approval.

How do I promote an episode to a rule in a knowledge management workflow?

Promote an episode to a rule by reading episodes.md, distilling the captured insight into a concise rule, and writing it to knowledge/rules.md. The source episodes are then marked as promoted to prevent duplicate processing.

What is episode-based learning for AI agents?

Episode-based learning is capturing difficult corrections and recurring issues into episodes.md. These episodes are then evaluated, distilled into structured knowledge, and promoted to formal rules to govern future agent flows.

Can I use automated rule promotion without overwriting protected files?

Yes, automated rule promotion integrates with safe, guarded automation. It aligns with top-level instruction files and protected flows, ensuring that only approved rules are written to rules.md while protected files remain untouched.

When do I need to convert complex insights into agent rules?

Convert complex insights into agent rules when recurring patterns or explicit user prompts indicate repeated mistakes. Capturing these difficult corrections as episodes prevents future drift and ensures consistent agent behavior across workflows.

Does agent self-learning require manual approval before writing new rules?

Yes, the three-step agent flow requires user approval before writing to rules.md. The system reads episodes.md, distills a rule, and only commits the knowledge to rules.md after explicit user confirmation, marking the source episode as promoted.