Aegis
Helps coding agents understand and maintain software architecture with baselines, evidence, and drift checks.
Project overview
Helps coding agents understand and maintain software architecture with baselines, evidence, and drift checks. Its core areas include Architecture awareness, Evidence verification, Drift checks. Start with the repository documentation and the smallest practical scope before adopting it broadly.
Core capabilities
Architecture awareness
Adds a repeatable workflow or integration for Architecture awareness.
Evidence verification
Adds a repeatable workflow or integration for Evidence verification.
Drift checks
Adds a repeatable workflow or integration for Drift checks.
Installation and usage
This usage path is based on the current public documentation for Aegis. Complete the steps in order before using it from your agent.
Let an AI Agent install it
Send this prompt to Codex, Claude Code, or another AI agent that can work with your local environment.
Help me install this DSH: Aegis
Project URL: https://github.com/GanyuanRan/Aegis
Read the README and installation files first, confirm the current environment and target directory, then follow the project's documented installation method. Run a minimal verification task afterward and report the install location, steps, and result. Ask before requesting credentials, additional permissions, overwriting files, or performing risky actions.- Prepare a compatible agent or runtime
- Confirm access to the local files or services required by the project
Project URL: https://github.com/GanyuanRan/Aegis#quick-install
Copy the URL and follow the steps below to complete setup.- 1Apply the configuration
Use the command or configuration above to add the resource to the current agent environment.
- 2Complete required setup
Complete path, permission, or connection settings for the current runtime.
- 3Run a minimal task
Run a minimal task in the agent. If the resource is recognized and returns the documented type of result, the setup is active.
Run a minimal task in the agent. If the resource is recognized and returns the documented type of result, the setup is active.
Use cases
You use DeepSeek Harness and want additional tools, interface features, or engineering workflows
Your current task needs Architecture awareness or Evidence verification
Assessment
Why it may be useful
- You use DeepSeek Harness and want additional tools, interface features, or engineering workflows
- Your current task needs Architecture awareness or Evidence verification
What to know first
- You do not have a DSH environment and the project does not document another host
- You want to use it in production without reading the repository documentation or reviewing permissions
README
Aegis
Overview
Helps coding agents understand and maintain software architecture with baselines, evidence, and drift checks. Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.
Getting started
- This usage path is based on the current public documentation for Aegis. Complete the steps in order before using it from your agent.
- Project focus: Helps coding agents understand and maintain software architecture with baselines, evidence, and drift checks.
- Published characteristics: Multi-host, 22 Skills, Architecture baseline.
- Run a minimal task in the agent. If the resource is recognized and returns the documented type of result, the setup is active.
Configuration
Project URL: https://github.com/GanyuanRan/Aegis#quick-install
Copy the URL and follow the steps below to complete setup.