What Better Agents Really Is
Page Contents
- What Better Agents Really Is
- Better Agents is essentially a project scaffolding and standards tool for building production-grade AI agents.
- Think of it as:
- Why Better Agents Exists
- The Core Benefit
- Breaking Down the Project Structure
- 1. app/ or src/
- 2. tests/scenarios/
- 3. tests/evaluations/
- 4. prompts/
- 5. prompts.json
- 6. AGENTS.md
- 7. .mcp.json
- 8. .env
- How This Transforms Your Development Workflow
Better Agents is essentially a project scaffolding and standards tool for building production-grade AI agents.
Think of it as:
Copilot / Claude Code / Cursor + Agent Framework (Agno, LangGraph, Mastra) + Industry Best Practices… bundled into a repeatable project template.
It gives you a standardized directory layout, prompt system, scenario tests, evaluation notebooks, and MCP integration so your coding assistant knows exactly how to help you build, extend, and test agents correctly. ~ Eric Schultz, Founder – Vibe Code Company
In simple terms:
It gives your VS Code coding assistant guardrails and patterns so it behaves like a real AI engineer working inside a real agent project.
Brought to you by Vibe Code Company
Why Better Agents Exists
Normally when people build agents, the project becomes messy:
- unclear prompts
- untested behaviors
- no versioning
- no evaluation
- fragile workflows
- poor maintainability
Better Agents solves that.
It forces a clean structure and gives your coding assistant the context it needs to produce accurate, production-ready updates.
The Core Benefit
Your AI coding assistant becomes capable of:
Building, editing, testing, evaluating, and versioning an agent the way a senior agent engineer would.
It is not just autocomplete.
It becomes deeply aware of:
- your framework
- your prompts
- your testing style
- your evaluation datasets
- your agent lifecycle
This is why the .mcp.json file is included:
It configures the tools your coding assistant is allowed to use (filesystem, shell, agents, tests, frameworks, etc).
Breaking Down the Project Structure
Here is a practical interpretation of each folder so you know what you’d actually put in it and why it matters.
1. app/ or src/
This is the heart of your agent.
Inside here lives your:
- agent graph or workflow
- tools
- message passing logic
- memory
- actions
- integrations
If you’re using LangGraph, this is where your nodes, edges, and orchestrator go.
If you’re using Agno, this is where your agent’s pipeline and tools go.
Your VS Code agent will understand this folder as the “live code” and maintain it using your chosen framework’s patterns.
2. tests/scenarios/
This is one of the biggest upgrades.
Scenario tests simulate real conversations with your agent.
They are end-to-end smoke tests like:
- “When the user asks for a summary, the agent fetches external data and returns a structured answer.”
- “When the agent hits a tool error, it retries correctly.”
- “When given bad input, the agent falls back gracefully.”
These are not unit tests.
They validate behavior, not just code.
Your coding assistant will write, update, and maintain these tests for you.
3. tests/evaluations/
This is where you evaluate:
- RAG quality
- classification accuracy
- routing logic
- summarization consistency
- any LLM step that has measurable output
Think: lightweight research notebooks.
This is how you benchmark improvements across versions.
4. prompts/
This is your version-controlled prompt library.
Each prompt is stored as YAML:
name: retrieval_instructions
version: 1.3
content: |
You are a retrieval agent...
Your coding assistant can:
- update prompts
- bump versions
- track changes
- compare performance across versions
This solves the industry’s #1 problem: prompt drift.
5. prompts.json
The registry file.
It keeps track of all prompt versions so:
- your assistant knows which prompt you’re referencing
- VS Code agent tooling knows which prompt to load
- your evaluation notebooks know what version they’re benchmarking
This lets multiple developers collaborate cleanly.
6. AGENTS.md
This is the governing document.
It contains:
- project conventions
- naming rules
- testing rules
- how to write scenarios
- how to write prompts
- how to integrate tools
- how to maintain versions
Your assistant reads this file constantly so it behaves like a team member following your standards.
7. .mcp.json
This configures tools exposed to your coding assistant.
It tells your AI developer:
- which commands it is allowed to run
- which tools or subsystems exist in the project
- how to interact with your framework
This is how Better Agents “trains” your coding assistant to be great at your chosen agent framework.
8. .env
Keys for:
- LLMs
- vector stores
- APIs
- databases
- agent tools
Your AI coding helper won’t expose these but will reference them.
How This Transforms Your Development Workflow
Inside VS Code, your workflow becomes:
- You describe a new feature.
- Your coding assistant:
- updates or creates the agent code
- writes the new prompt or modifies existing ones
- writes the scenario test for the new behavior
- updates the prompt version and registry
- optionally creates an evaluation notebook
- You run tests.
- You get a stable production agent.
This is the closest thing to having an actual engineering team backing your agent builds.
I hope this article on better agents has been helpful for you. It is brought to you by our partner company, Vibe Code Company.
Learn more about Vibe Code Company at https://VibeCodeCompany.com
Have fun with your new Better Agent – Eric, Founder & CEO – WebSuite Media | Vibe Code Company
