agent-architecture-audit

Editorial and source context

What this Skill does

Agent Architecture Audit is a source-indexed Agent Skill for development & engineering work. Based on the SKILL.md description, it focuses on full-stack diagnostic for agent and llm applications. Use the linked GitHub file to confirm scope and prerequisites before enabling it.

What the author says

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

Compatibility and requirements

• Use an agent runtime that supports Agent Skills and the linked SKILL.md format.
• Confirm the source repository's tools, SDKs, and platform prerequisites for ui and frontend work.

How to install or import it

• Open the linked GitHub SKILL.md and review its scope and setup instructions.
• Install or import the skill using the agent runtime's documented workflow.
• Run a small, non-sensitive test and verify the output before broader use.

Permissions and risks

• Review every command, file path, network request, dependency, and credential scope before enabling it.
• GitHub stars indicate popularity, not safety or correctness; validate the source and test with non-sensitive data.

Example workflows

• Ask an AI agent to apply Agent Architecture Audit to ui and frontend work described in the source record.
• Have the agent state assumptions, required tools, and expected output before using this development & engineering skill.
• Compare the result with the linked GitHub SKILL.md and verify it against your project requirements.