YMD/PMD format specification and authoring tools for structured, modular AI prompts
This plugin is not yet in any themed marketplace. To install it, you'll need to add it from GitHub directly.
Choose your preferred installation method below
A marketplace is a collection of plugins. Every plugin gets an auto-generated marketplace JSON for individual installation, plus inclusion in category and themed collections. Add a marketplace once (step 1), then install any plugin from it (step 2).
One-time setup for access to all plugins
When to use: If you plan to install multiple plugins now or later
Step 1: Add the marketplace (one-time)
/plugin marketplace add https://claudepluginhub.com/marketplaces/all.jsonRun this once to access all plugins
Step 2: Install this plugin
/plugin install gradient@allUse this plugin's auto-generated marketplace JSON for individual installation
When to use: If you only want to try this specific plugin
Step 1: Add this plugin's marketplace
/plugin marketplace add https://claudepluginhub.com/marketplaces/plugins/gradient.jsonStep 2: Install the plugin
/plugin install gradient@gradientA proposal for a layered context architecture
Gradient defines architectural patterns for building layered context injection systems for Claude Code plugins, emphasizing smooth transitions from normative specifications through applied context to dynamic orchestration.
███▓▓▒▒░░░░ SPECS (The WHAT - Normative)
███▓▓▒▒░░ CONTEXT (The HOW - Applied)
██▓▓▒▒ PROMPTS (The ACTION - Orchestration)
Gradient is an architectural framework for organizing Claude Code plugins and context injection systems. It emerged from patterns discovered while building projects like ymd-spec, semantic-docstrings, and code-zen.
Instead of rigid, isolated layers, Gradient promotes smooth transitions between architectural layers:
Like a gradient, each layer dissolves into the next, creating a fluid, organic architecture.
@ references for specsgradient/
├── gradient/spec/ # SPECS: Normative (The WHAT)
│ ├── architecture-spec.md
│ ├── anti-duplication-principles.md
│ └── layer-spec.md
│
├── context/ # CONTEXT: Applied (The HOW)
│ ├── examples.md
│ ├── implementation-guide.md
│ └── decision-guide.md
│
├── prompts/ # PROMPTS: Orchestration (The ACTION)
│ └── load-context.md # Thin loader with @ references
│
├── commands/ # COMMANDS: Entry points (API)
│ └── *.md # One-to-one with prompts
│
├── agents/ # AGENTS: Specialized contexts
│ └── *.md # Spin-off processes
│
└── docs/ # DOCS: Human documentation
└── *.md # Architecture guides, tutorials
SPECS (Normative):
CONTEXT (Applied):
PROMPTS (Orchestration):
@ referencesLayers blend into each other:
Like REST routes, commands are thin entry points:
<!-- commands/load-gradient-context.md -->
@~/.claude/gradient/prompts/load-context.md
One-to-one mapping with prompts. Commands define the interface, prompts orchestrate the logic.
Specialized contexts with separate permissions:
<!-- agents/architecture-reviewer.md -->
You are an architecture reviewer for Gradient projects.
@~/.claude/gradient/gradient/spec/architecture-spec.md
@~/.claude/gradient/context/decision-guide.md
Run independently, return summarized results without contaminating main context.
Triggered by Claude Code lifecycle events (not yet explored in this project).
When code is more efficient than tokens:
# scripts/validate-structure.sh
# Validate Gradient architecture compliance
Documentation Site: Visit the complete documentation site (when published) with interactive examples and guides.
Local development: Run the Jekyll site locally:
cd docs
bundle exec jekyll serve
# Access at http://localhost:4000
Quick reads:
Load the architecture spec:
@~/.claude/gradient/gradient/spec/architecture-spec.md
@~/.claude/gradient/gradient/spec/anti-duplication-principles.md
Status: In Development
This project is actively being developed as a distillation of patterns from:
ymd-spec: YMD/PMD format specificationsemantic-docstrings: Semantic documentation standardscode-zen: Zen of Python implementation guide"Architecture isn't about rigid layers—it's about smooth, intentional transitions."
Gradient recognizes that effective context injection requires:
Like a gradient in design, our architecture dissolves boundaries while maintaining distinct identities.
Complete documentation with interactive examples, Mermaid diagrams, and step-by-step guides:
MIT License - See LICENSE file for details
Contributions welcome! This project aims to establish patterns for Claude Code plugin architecture. Share your insights and patterns.
Gradient - From specs to action, smoothly.
0.1.0