Skill Optimization

Skill Optimization is an AI Engineering skill for Claude Code, published by shinpr in ai-coding-project-boilerplate.

227 stars25 forkson shinpr/ai-coding-project-boilerplateAdded 2026/09/03Repository updated 2026/09/01

agent-skillsagentic-aiagentic-workflowai-agentsanthropicboilerplateclaude-codecontext-engineeringdeveloper-toolsllm-orchestrationproductivityquality-gatestypescript

Install in seconds

Install Skill Optimization

Copy Skill Optimization into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/shinpr/ai-coding-project-boilerplate/tree/main/.claude/skills-en/skill-optimization ~/.claude/skills/skill-optimization

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/shinpr/ai-coding-project-boilerplate.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: .claude/skills-en/skill-optimization/SKILL.md in shinpr/ai-coding-project-boilerplate
Installs to: ~/.claude/skills/skill-optimization
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2793 skills

What Skill Optimization does

Skill Optimization evaluates and refines skill files using content patterns and editing principles. Use it when creating, auditing, or revising skill content for clearer execution and more consistent structure.

Skill Optimization is cataloged under AI Engineering on DirSkills. Skill Optimization comes from a repository tagged agent-skills, agentic-ai, agentic-workflow, ai-agents and anthropic.

Documentation

README

Excerpt

Skill Content Optimization

Core Philosophy

Finding-Based: Every change resolves a recorded issue or follows a named project-specific source
Concrete: Each pattern provides detection criteria and transform methods
Structure-Focused: Optimizes expression and organization; domain knowledge remains unchanged
Intent-Preserving: Records the original requirements before changing structure, wording, constraints, context, or examples
Traceable: Connects every applied change to a finding or named project source
Self-Contained: Keeps every pure skill executable when loaded alone; duplication across independently loaded pure skills is valid when each copy is required for standalone execution

Content Optimization Patterns

P1: Critical (Must Fix)

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Skill Optimization

What else does shinpr publish alongside Skill Optimization?
Skill Optimization is one of 25 skills that DirSkills catalogs from shinpr/ai-coding-project-boilerplate, the repository it ships in. Its siblings there include Coding Standards, Coding Standards and Create Skill. Each one is a separate skill with its own page in this directory, installs the same way Skill Optimization does, and is maintained by shinpr in that same repository. The rest of the collection is listed on the shinpr/ai-coding-project-boilerplate page.
How does Skill Optimization compare to other AI Engineering skills?
Skill Optimization ranks #2515 by stars among the 2793 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Skill Optimization against them. Open each page to compare what they document and how they install.