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Self-Reflection

Evaluate completed work and route reusable lessons to self-improving memory.

Updated Mar 30, 2026
Search Tags:#routing#evaluation#memory#reflection#lessons#post-task
One-click install
npx skills add https://github.com/harkers/forge-email-server --skill self-reflection-harkers
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Self-Reflection
Source: https://github.com/harkers/forge-email-server/tree/main/self-reflection-skill
Command: npx skills add https://github.com/harkers/forge-email-server --skill self-reflection-harkers

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-task evaluation skill for comparing outcome vs intent, identifying quality gaps, and routing reusable lessons into self-improving memory. Use when (1) a multi-step task completes; (2) a bug or negative feedback; (3) a fix is applied; (4) the output could be better; (5) the user references the skill for the current task.

Core Features & Use Cases

  • It serves as the evaluation layer, extracting lessons and routing them by scope.
  • It defines a lightweight flow: task completion → reflect briefly → classify lesson → decide storage → hand reusable lesson to self-improving.
  • It enforces separation between reflection and memory to keep systems lean.

Quick Start

After meaningful work, perform a brief post-task review using the reflection template and route the lesson only if it is reusable.

Frequently Asked Questions about Self-Reflection

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

FAQPage Schema
How do I extract reusable lessons from completed tasks and bug fixes?▼

Perform a post-task reflection by comparing outcome versus intent to identify quality gaps, then route evidence-based lessons into structured memory files like corrections.md or domains/<domain>.md for future reuse.

What is post-task evaluation and how does it improve future work quality?▼

Post-task evaluation reviews completed work to identify gaps between intent and outcome, extracting actionable lessons and routing them into scoped memory to prevent repeating mistakes and drive repeatable improvements.

How do I organize and route lessons learned by scope after a project?▼

Route lessons learned by scope: discard non-reusable insights, save general corrections to corrections.md, domain-specific lessons to domains/<domain>.md, and project-specific actions to projects/<project>.md.

When should I run a post-task reflection on my work output?▼

Run a post-task reflection after completing multi-step tasks, applying bug fixes, receiving negative user feedback, or whenever output required rework and could be better, ensuring insights are captured immediately.

Do I need a specific framework to format post-task reflections?▼

No external framework is needed. Format post-task reflections using the standard CONTEXT, INTENT, OUTCOME, GAP, LESSON, and ACTION structure to enforce concise, evidence-based documentation before routing to memory.

What's the best way to separate reflection logic from memory storage?▼

The best way to separate reflection from memory is to classify the lesson during evaluation, decide its storage scope, then hand the reusable lesson directly to a self-improving memory system to keep the architecture lean.

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