Rules in CodeLLM help you guide your AI coding agent with specific instructions - from coding style preferences to architectural decisions, project templates, and even how the assistant talks to you. Think of them as reusable, always-on instructions that act like a persistent memory for your assistant - ensuring consistency in your workflows, across files and sessions.
Large language models don’t retain memory between tasks. Rules solve this by injecting persistent context into your AI prompts — helping the assistant respond consistently across your files and projects.
Whenever a Rule applies, its contents are included automatically at the start of the model’s context.
Rules apply in:
They are scoped using two settings:
routes/api/*.ts
)You may find the different rules here in this Rule directory and add them to the list - https://rules.abacusai.app/
Help CodeLLM understand project-specific terms and logic while helping you coding and providing suggestions.
description: "Domain-specific terminology and conventions"
globs: ["*"]
ruleType: always
---
- In our app, 'Tenant' refers to an organization, not an individual user.
- The 'Account' model handles billing relationships.
- 'Subscription' controls feature access levels and is always linked to a Tenant.
📌 Tip: Add to .codellm/rules to apply across the project.
Define reusable templates for common tasks.
description: "API endpoint boilerplate"
globs: ["routes/api/*.ts"]
ruleType: auto-attached
---
Use this template for new API routes:
```ts
import { NextApiRequest, NextApiResponse } from 'next'
import { withAuth } from '@/lib/auth'
export default withAuth(async function handler(req: NextApiRequest, res: NextApiResponse) {
// Your code here
})
```
- All endpoints must use withAuth
- Validate request payloads using zod
Enforce how code should be structured across the team.
description: "React component guidelines"
globs: ["components/**/*.tsx"]
ruleType: always
---
- Use functional components (avoid class components)
- Follow PascalCase for naming (e.g., `UserProfile`)
- Component file layout:
- Main component
- Subcomponents
- Styles
- Tests
- Avoid inline styles; prefer styled-components
Control how the assistant talks — great for teams or non-English settings.
description: "Formal French tone"
globs: ["*"]
ruleType: always
---
- Respond in fluent French
- Use a formal, documentation-style tone
- Keep responses short and precise with code examples
Adapt the response style to your coding proficiency and learning style. Really helpful for non-technical users and beginners for setting up the style in a manner that you can understand
description: "Non-technical communication style and support"
globs: ["*"]
ruleType: always
---
- Adjust responses to match the proficiency of a non-technical user.
- When suggesting a tool, code, or task, always include brief background context to explain:
- Why the task is important
- When it is typically needed
- How it fits into the bigger picture
- If the task involves manual steps (e.g., command-line use, file changes, or UI navigation), provide:
- Clear step-by-step instructions
- Expected outcomes or changes after each step
- Any prerequisites, dependencies, or files the user should check beforehand
- Use code comments to explain logic instead of long paragraphs
Open a Folder in CodeLLM
Search for Rule in the Main search bar with the given string >Rule
and click on Create Rule.
This adds a .codellm/rules/
folder to your project with the given file name
Fill out the following details:
📌 Tip: You can also copy-paste existing rule files between projects!
✅ Good Practice | ❌ Avoid This |
---|---|
Be specific and actionable | Vague guidance like "write clean code" |
Keep rules modular | One giant rule covering everything |
Add concrete examples | Generic instructions without context |
Use globs smartly | Overusing * everywhere |
Test your rules on sample files | Assuming it works without trying |
Yes, absolutely! Just make sure they don’t conflict with each other and are not ambiguous.
Yes, just mention it in your prompt with @file
to attach it manually.
For further assistance, please contact our support team: support@abacus.ai.