---
title: "agentic-bundle-agent-architect"
description: "Portable skills-only \"Agent Architect\" plugin from Agentic Awesome Skills."
canonical: https://agentpluginsdirectory.com/plugins/agentic-bundle-agent-architect--costrict-plugins-repo
last-updated: 2026-10-21
---

# agentic-bundle-agent-architect
Portable skills-only "Agent Architect" plugin from Agentic Awesome Skills.
- Slug: agentic-bundle-agent-architect--costrict-plugins-repo
- Publisher: sickn33 and contributors
- Repository: https://github.com/costrict-plugins-repo/sickn33-agentic-awesome-skills-agentic-bundle-agent-architect
- Manifest: plugin.json
- Version: 16.5.0
- License: MIT
- Category (editorial): agent-tooling
- Skills: 7 (agent-evaluation, agent-memory-systems, ai-agents-architect, langgraph, mcp-builder, prompt-engineering, rag-engineer)
- MCP servers: 0
- Stars: 0
- Repository created: 2026-09-01
- Repository last pushed: 2026-09-01
- Publisher type: Organization
- Listing: https://agentpluginsdirectory.com/plugins/agentic-bundle-agent-architect--costrict-plugins-repo
- Schema: https://agent-plugins.org/schemas/1.0.0/plugin.schema.json

## Skills

- agent-evaluation: Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring, where even top agents achieve less than 50% on real-world benchmarks
- agent-memory-systems: Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
- ai-agents-architect: Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.
- langgraph: Expert in LangGraph: the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.
- mcp-builder: Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
- prompt-engineering: Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
- rag-engineer: Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.

Descriptions come from the frontmatter of each SKILL.md, punctuation lightly normalized.