documentation-standards
v1.0.1HADS (Human-AI Document Standard) — semantic tagging convention for writing documentation that works efficiently for both human readers and AI models. Reduces token consumption and hallucination risk by separating machine-critical facts from human context.
By Niksa BarlovicLicense: MIT0 GitHub starsUpdated 4 months ago
Directory evidence
- Runtimes
- Claude Code
- Parsed components
- 1 skill or MCP entry
- Source updated
- Jun 22, 2026
- Manifest status
- Canonical path parsed
The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →
Install documentation-standards for Claude Code
claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install documentation-standards-4@agent-plugin-marketplacePaste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.
The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.
Get the source manually
git clone https://github.com/yo-steven/agents-exploration-20260523Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/documentation-standards/.
Plugin files
├── .claude-plugin/plugin.json└── skills/hads/SKILL.md
Included Skills1
Use when writing technical documentation that needs to be readable by both humans and AI models, converting existing docs to HADS format, validating a HADS document, or optimizing documentation for token-efficient AI consumption.
Plugin manifests1
{
"name": "documentation-standards",
"version": "1.0.1",
"description": "HADS (Human-AI Document Standard) — semantic tagging convention for writing documentation that works efficiently for both human readers and AI models. Reduces token consumption and hallucination risk by separating machine-critical facts from human context.",
"author": {
"name": "Niksa Barlovic",
"email": "[email protected]"
},
"license": "MIT"
}For maintainers
If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.
[documentation-standards on Agent Plugins Marketplace](https://pluginsmp.com/plugins/documentation-standards-4)