How does the maturity scoring work?

The skill assesses 12 specific grades across three classes. Your level is determined by the highest consecutive grade achieved, ensuring a stable foundation before moving to complex orchestration.

What indicators does this skill look for?

It scans for the existence of CLAUDE.md files, .claude/ directory structures, sub-agent definitions, custom skills, prompt chains, and external webhook triggers.

What is an agentic layer?

An agentic layer is a specialized set of prompts, tools, sub-agents, and workflows configured within a codebase to enhance how AI models understand and manipulate that specific project.

Why is the 12-grade system important?

Building an autonomous coding environment requires a step-by-step progression; skipping foundational steps like memory files or validation loops often leads to unstable AI behavior in production.

Agentic Layer Assessment

Name: Agentic Layer Assessment
Author: melodic-software

bymelodic-software

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生产力与工作流

Evaluates the maturity of a codebase's AI agentic infrastructure using a standardized 12-grade classification system.

关于

The Agentic Layer Assessment skill provides a comprehensive framework for auditing and improving the AI-driven capabilities of any codebase. Based on the TAC (The Agentic Company) methodology, it scans for architectural patterns like memory files, sub-agent definitions, and autonomous workflows to assign a maturity score across three distinct classes: Foundation, External Integration, and Production Orchestration. This skill is essential for developers looking to transition from basic AI assistance to high-level automation by identifying specific technical gaps and providing a structured roadmap toward Codebase Singularity.

主要功能

Automated codebase scanning for agentic patterns and indicators
Actionable recommendations for achieving the next maturity grade
12-grade maturity scoring across Foundation, Integration, and Orchestration classes
Evidence-based reporting on memory files, sub-agents, and prompt chains
Audit support for AI Developer Workflows (ADWs) and orchestrator setups
12 GitHub stars

使用场景

Onboarding new team members to project-specific agentic patterns
Evaluating codebase readiness for autonomous AI agents
Planning infrastructure investments for AI-driven development cycles

关于

主要功能

Automated codebase scanning for agentic patterns and indicators
Actionable recommendations for achieving the next maturity grade
12-grade maturity scoring across Foundation, Integration, and Orchestration classes
Evidence-based reporting on memory files, sub-agents, and prompt chains
Audit support for AI Developer Workflows (ADWs) and orchestrator setups
12 GitHub stars

使用场景

Onboarding new team members to project-specific agentic patterns
Evaluating codebase readiness for autonomous AI agents
Planning infrastructure investments for AI-driven development cycles