Files
awesome-copilot/plugins/context-engineering
Aaron Powell 9d1df57ebc refactor: migrate plugins to Claude Code spec format
- Move plugin manifests from .github/plugin/ to .claude-plugin/
- Convert items[] to Claude Code spec fields (agents, commands, skills)
- Rename tags to keywords, drop display/featured/instructions from plugins
- Delete all symlinks and materialized files from plugin directories
- Add eng/materialize-plugins.mjs to copy source files into plugin dirs at publish time
- Add .github/workflows/publish.yml for staged->main publishing
- Update CI triggers to target staged branch
- Update validation, creation, marketplace, and README generation scripts
- Update CONTRIBUTING.md and AGENTS.md documentation
- Include all new content from main (polyglot-test-agent, gem-browser-tester,
  fabric-lakehouse, fluentui-blazor, quasi-coder, transloadit-media-processing,
  make-repo-contribution hardening, website logo/gradient changes)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-02-18 14:22:50 +11:00
..

Context Engineering Plugin

Tools and techniques for maximizing GitHub Copilot effectiveness through better context management. Includes guidelines for structuring code, an agent for planning multi-file changes, and prompts for context-aware development.

Installation

# Using Copilot CLI
copilot plugin install context-engineering@awesome-copilot

What's Included

Commands (Slash Commands)

Command Description
/context-engineering:context-map Generate a map of all files relevant to a task before making changes
/context-engineering:what-context-needed Ask Copilot what files it needs to see before answering a question
/context-engineering:refactor-plan Plan a multi-file refactor with proper sequencing and rollback steps

Agents

Agent Description
context-architect An agent that helps plan and execute multi-file changes by identifying relevant context and dependencies

Source

This plugin is part of Awesome Copilot, a community-driven collection of GitHub Copilot extensions.

License

MIT