mjs-skills

Personal skill library that compounds value over decades.
Skills are not tools. They are frozen decisions.
Each skill encodes judgment about what matters, what fails, and what works.

What This Is

A curated collection of Agent Skills — reusable units of intelligence that teach AI coding agents how to perform specific tasks autonomously.

Each skill encodes:

• What matters here? (focus)
• What can go wrong? (guardrails)
• What is the fastest correct path? (judgment)
• How do I know I'm done? (verification)

Philosophy

Traditional: You write code → Code runs → Application works
Agentic:     You write Skills → AI learns patterns → AI writes code → Application works

The bar is higher than MIT, OpenAI, or Google — because this optimizes for personal throughput, context dominance, and problem-to-solution compression, not coordination, publication, or scale.

Core Rule

If two skills plausibly trigger on the same query, at least one is incorrectly designed.

Structure

mjs-skills/
├── .claude/
│   ├── skills/                    # The actual skills (22 total)
│   │   ├── meta/                  # Skills about skills
│   │   ├── mcp-powered/           # MCP server wrappers
│   │   ├── infrastructure/        # K8s & cloud
│   │   ├── application/           # Service scaffolding
│   │   ├── ui-patterns/           # Chat & frontend
│   │   ├── integration/           # Connecting services
│   │   ├── devops/                # Deployment & docs
│   │   └── voice/                 # Voice interfaces
│   │
│   ├── hooks/                     # Evaluation & tracking
│   │   ├── track-prompt.sh        # Log user prompts
│   │   ├── track-skill-start.sh   # Detect skill activation
│   │   ├── track-skill-end.sh     # Capture verify.py results
│   │   └── analyze-skills.py      # Weekly usage analysis
│   │
│   └── activity-logs/             # Passive data collection
│       ├── prompts.jsonl
│       └── skill-usage.jsonl
│
├── research/                      # Design documents
│   ├── skill-design-reference.md  # How to build skills
│   ├── h3-skills-master-prd.md    # What skills to build
│   └── skills-evaluation-prd.md   # How to measure value
│
├── spec/                          # Agent Skills Specification
│   └── ...                        # (cloned from agentskills.io)
│
├── CONSTITUTION.md                # Governance principles
└── README.md                      # You are here

Skill Anatomy

skill-name/
├── SKILL.md              # YAML frontmatter + instructions (~300 tokens)
├── scripts/
│   ├── verify.py         # Returns 0 (success) or 1 (failure)
│   └── deploy.sh         # Optional: execution script
├── references/           # Optional: deep docs (loaded on-demand)
└── templates/            # Optional: reusable scaffolds

SKILL.md Format

---
name: deploying-kafka-k8s
description: |
  Deploys Apache Kafka on Kubernetes using Helm.
  Use when setting up event streaming or pub/sub messaging.
---

## Quick Start
[Immediate action - the 80% case]

## Instructions
1. [Step with command]
2. [Validation step]

## If Verification Fails
[Diagnostic commands + escalation]

Hooks: Zero-Overhead Measurement

Claude Code hooks automatically track skill usage without manual intervention.

How Skills Get Detected

When Claude activates a skill, it reads the SKILL.md:

cat /path/to/.claude/skills/deploying-kafka-k8s/SKILL.md

PreToolUse hook detects this pattern → logs to skill-usage.jsonl

Data Flow

User prompt 
    → UserPromptSubmit hook logs prompt
    → Claude reads SKILL.md (via cat/view)
    → PreToolUse hook detects skill activation
    → Skill executes
    → verify.py runs
    → PostToolUse hook captures success/failure
    → skill-usage.jsonl contains full trace

What You Get (Free)

Quick Start

1. Clone

git clone https://github.com/mshaukat/mjs-skills.git
cd mjs-skills

2. Install Hooks

chmod +x .claude/hooks/*.sh
# Add hook config to ~/.claude/settings.json (see research/skills-evaluation-prd.md)

3. Use a Skill

In Claude Code:

Deploy Kafka on my local Kubernetes cluster

Claude will:

1. Find deploying-kafka-k8s skill
2. Load SKILL.md into context
3. Execute the deployment
4. Run verify.py to confirm success

4. Analyze (Weekly)

python .claude/hooks/analyze-skills.py

Routing Evaluation

Before shipping any skill, test routing:

The Ultimate Value Test

Would you recreate this skill if it were deleted?

If no → delete it.

Research Documents

Compatibility

Skills work across:

• Claude Code
• Goose (AAIF Standard)
• OpenAI Codex
• Any agent supporting the Agent Skills Specification

Skills are frozen decisions. The goal is not to do less work, but to do the right work faster—and know why it works.