Skip to content
Back to skills

Architecture Refinement

ASecurity

Meta-skill for maintaining and evolving Alex's cognitive architecture through deliberate documentation and pattern extraction.

  • 4 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added September 3, 2026
ai-agentsgogitdocumentation

Security analysis

A100/100

Scanned September 3, 2026

npx -y skills add fabioc-aloha/Alex_Skill_Mall --skill architecture-refinement --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Architecture Refinement?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Architecture Refinement
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/fabioc-aloha-architecture-refinement/badge)](https://www.skillsdirectory.com/skills/fabioc-aloha-architecture-refinement)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: architecture-refinement
description: "Meta-skill for maintaining and evolving Alex's cognitive architecture through deliberate documentation and pattern extraction."
lastReviewed: 2026-04-30
---

# Architecture Refinement Skill


> Meta-skill for maintaining and evolving the AI assistant's cognitive architecture through deliberate documentation and pattern extraction.

## Purpose

This skill enables the AI assistant to:

- Recognize when a learning session produces architecture-worthy insights
- Document patterns in the appropriate .github/ location (skills, instructions, prompts)
- Update migration trackers and status tables
- Consolidate knowledge files following KISS/DRY principles

## When to Apply

Trigger this skill when:

- A session resolves a recurring problem (document the pattern)
- A skill file is migrated or consolidated (update trackers)
- A new workflow emerges (capture in appropriate .instructions.md)
- User feedback reveals a principle ("don't over-simplify")

## Core Patterns

### Pattern Recognition Checklist

Before session ends, ask:

| Question | If Yes → Action |
| -------- | --------------- |
| Did we solve a problem that could recur? | Document in relevant skill file |
| Did we learn something about the AI assistant's architecture? | Update relevant .github/ documentation |
| Did a file get created/deleted/consolidated? | Update migration trackers |
| Did user correct AI behavior? | Add to skill's Anti-Patterns + document principle |
| Did the skill itself get improved during use? | Commit the refinement immediately |

### Documentation Location Guide

| What You Learned | Where to Document | Audience |
| ---------------- | ----------------- | -------- |
| Technical skill pattern | `.github/skills/{name}/SKILL.md` | the AI assistant (AI) |
| Important concepts for user | `.github/skills/{name}/SKILL.md` | Human + AI |
| Process improvement | `.github/instructions/*.instructions.md` | the AI assistant (AI) |
| Complex workflow | `.github/prompts/*.prompt.md` | the AI assistant (AI) |
| Domain expertise | `.github/skills/{name}/SKILL.md` | the AI assistant (AI) |

**Key Distinction**:

- `.github/skills/` = Operational reference during work (the AI assistant + user)

### Consolidation Decision Tree

- **>50% overlap** with existing skill → Consolidate INTO it, update tracker as "Consolidated"
- **<50% overlap** → Create new skill, add to tracker as "Migrated"

### Pattern Extraction Template

When documenting a learned pattern:

```markdown
### [Pattern Name]

**Pattern**: [One-sentence description of what to do]

**Example**: [Concrete instance from the session]

**Why**:

- [Reason 1]
- [Reason 2]

**Anti-pattern**: [What NOT to do, if applicable]
```

## Quality Checks

Before committing documentation updates:

- [ ] Markdown lint-clean (blank lines around lists, proper headings)
- [ ] Tables have header separators
- [ ] No orphaned references to deleted files
- [ ] Migration trackers reflect current state
- [ ] Commit message follows conventional format

## Anti-Patterns

| Don't | Do Instead |
| ----- | ---------- |
| Document every minor fix | Only architecture-worthy insights |
| Create new file for each learning | Consolidate into existing structure |
| Wait until end of session | Document as patterns emerge |
| Over-document obvious things | Focus on non-obvious learnings |
| Skip human feedback | Capture corrective principles explicitly |

## User Coaching Learning Loop

User corrections = high-value learning.

**Protocol**: Acknowledge → Fix → Extract principle → Document in skill → Commit

| AI Tendency | User Correction | Extracted Principle |
| ----------- | --------------- | ------------------- |
| Over-centralize | "Don't dump in one file" | Distribute to appropriate locations |
| Over-simplify | "You lost context" | Preserve nuance when consolidating |
| Skip validation | "Did you check it?" | Always verify (lint, count chars) |
| Assume completion | "What about X?" | Follow through on all aspects |
| Add diagrams to skills | "KISS them goodbye" | Skills are for AI, not visual learners |

---

## Connection to Bootstrap Learning

Learn → Coach → Extract → Document → Consolidate

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.