What is the primary purpose of the using-skills protocol?

It acts as a meta-governance layer that ensures Claude uses the correct specialized skills and tools, such as prioritizing the look-at tool over the Read tool for media, to maintain efficiency.

What are the 'Iron Laws' mentioned in the skill?

These are non-negotiable rules regarding multimodal file analysis and the mandatory inclusion of description parameters in bash calls to ensure professional and debuggable output.

Does the user need to manually trigger this skill?

No, this skill is designed to be auto-loaded at session start via a SessionStart hook to provide foundational discipline for all interactions.

How does it handle bug reports?

It mandates a systematic approach using a Ralph Loop and prevents Claude from reading code files or investigating independently until the structured workflow is initiated.

How does this skill help with context window limits?

By enforcing the use of the look-at tool for media and PDFs, it extracts only necessary information, reducing token usage by over 95% compared to standard file reading.

Skill Orchestration Protocol

Name: Skill Orchestration Protocol
Author: edwinhu

byedwinhu

Productividad y Flujo de Trabajo

Enforces standardized skill invocation, optimized tool selection, and context-efficient media analysis for Claude Code sessions.

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The Skill Orchestration Protocol serves as a foundational meta-skill that governs how Claude interacts with all other specialized capabilities. It implements a strict decision-making framework for skill invocation, preventing redundant calls and ensuring that the most token-efficient tools are used for every task. By enforcing 'Iron Laws' for multimodal analysis and structured debugging loops, it maximizes context window efficiency and ensures Claude adheres to high-performance production patterns throughout the entire development lifecycle.

Características Principales

Optimized multimodal analysis using look-at to save 95%+ tokens
Automated skill invocation logic and trigger word detection
Enforcement of standardized bash call patterns and metadata
0 GitHub stars
Mandatory structured bug investigation and Ralph-loop protocols
Red-flag detection to prevent workflow skipping and context bloat

Casos de Uso

Standardizing AI behavior and workflow discipline across complex engineering projects
Optimizing context usage during media-heavy tasks involving images or PDFs
Implementing strict debugging and feature development sequences for high-reliability code

Acerca de

Características Principales

Optimized multimodal analysis using look-at to save 95%+ tokens
Automated skill invocation logic and trigger word detection
Enforcement of standardized bash call patterns and metadata
0 GitHub stars
Mandatory structured bug investigation and Ralph-loop protocols
Red-flag detection to prevent workflow skipping and context bloat

Casos de Uso

Standardizing AI behavior and workflow discipline across complex engineering projects
Optimizing context usage during media-heavy tasks involving images or PDFs
Implementing strict debugging and feature development sequences for high-reliability code