When should I use the max-quality-150 skill?

Invoke this skill for critical tasks like production deployments, security-sensitive changes, complex architectural decisions, or any scenario where the cost of an error is high.

How does this differ from standard AI coding responses?

Unlike standard responses that may use fragments, this skill mandates reading full files, exploring at least three alternative solutions, and identifying potential failure modes before delivering results.

Does using this skill make the AI slower?

It involves a more thorough process which may take slightly longer than a standard response, but it is designed to save time overall by preventing costly mistakes and rework.

Can I combine this with other Claude Code skills?

Yes, it is specifically designed to work alongside skills like 'deep-think-150' to provide a comprehensive high-quality reasoning and execution pipeline.

Max-Quality 150 Protocol

Name: Max-Quality 150 Protocol
Author: MykhailoDmytriakha

byMykhailoDmytriakha

Productivity & Workflow

Ensures maximum thoroughness and 150% coverage for critical development tasks and complex problem-solving.

About

The Max-Quality 150 Protocol is a high-integrity execution framework for Claude that mandates a '100% core + 50% strengthening' approach to software development. It transforms standard AI outputs into production-grade solutions by enforcing deep context reading, multi-perspective analysis, and rigorous risk assessment. This skill is specifically designed for mission-critical scenarios where accuracy is non-negotiable, providing users with documented reasoning, verified assumptions, and explicit confidence scores for every deliverable.

Key Features

Explicit confidence level reporting with numerical certainty scores
Multi-solution exploration evaluating at least three alternative approaches
Full context analysis including complete file reads and dependency tracking
Evidence-based verification of technical assumptions
Rigorous risk identification and mitigation planning
0 GitHub stars

Use Cases

Security-critical code reviews and authentication logic implementation
Architecting complex multi-system integrations with high technical debt
Executing production deployments where the cost of error is high

About

Key Features

Explicit confidence level reporting with numerical certainty scores
Multi-solution exploration evaluating at least three alternative approaches
Full context analysis including complete file reads and dependency tracking
Evidence-based verification of technical assumptions
Rigorous risk identification and mitigation planning
0 GitHub stars

Use Cases

Security-critical code reviews and authentication logic implementation
Architecting complex multi-system integrations with high technical debt
Executing production deployments where the cost of error is high