Product - Stop Re-Explaining Your Standards to AI

Install them once, AI remembers forever.

Context packs inject professional knowledge directly into your repository, so AI generates output that matches standards β€” consistently, without re-explaining.

Not a senior engineer? Context packs are even more valuable β€” you're importing professional standards and best practices directly into your codebase. Get consistent, high-quality output without needing years of experience or expensive consulting.

Buy Pack 01 β€” Β£119

One-time purchase β€’ Install in 5 minutes

Install in 5 minutes
Lives in your repo
Cursor & Claude ready

This Isn't a Prompt Library

Context packs are standards, rules, and workflows that live in your repository. They're not prompts you copy-paste β€” they're enforceable guardrails that AI automatically follows. Think of it as installing a senior engineer's expertise directly into your codebase, where it stays permanently.

❌ Prompt Library

  • β€’ Copy-paste prompts
  • β€’ Manual activation
  • β€’ Easy to forget
  • β€’ No enforcement

βœ… Context Pack

  • β€’ Standards live in your repo
  • β€’ Automatic enforcement
  • β€’ Always active
  • β€’ Version controlled

How it works

Install standards for you and AI to work from

1

Install CLI

Run: npm install -g @zebralabs/context-cli

2

Get a Pack

Purchase select 'knowledge packs' from our registry to solve specific problems

3

Install & Use

Run: ctx pack install to install standards into your repository

Now you have standards and knowledge imported into your codebase aligning you and your team (human/AI) - without the expensive senior software engineer consultation costs.

What Happens After Installation

Once installed, the pack becomes part of your repository and works automatically.

1. Cursor Rules

.cursor/rules/

  • β€’ Automatically loaded
  • β€’ AI follows these rules in every conversation
  • β€’ No activation needed
  • β€’ Rules organized by category (pack-specific)

2. Cursor Skills

.cursor/skills/

  • β€’ On-demand workflows
  • β€’ Invoke by name when you need step-by-step guidance
  • β€’ Specialized workflows for common tasks
  • β€’ Skills vary by pack (pack-specific)

3. Standards & Templates

docs/practices-and-standards/

  • β€’ Complete methodology and templates
  • β€’ AI references these when generating output
  • β€’ Version controlled with your code
  • β€’ Evolve with your team

See the Difference

Without vs. With Context Packs

Without Context PacksWith Context Packs
You ask: "Create a component spec"
β†’ AI creates different structure each time, missing sections, inconsistent format
You ask: "Create a component spec"
β†’ AI creates the same structure every time, all required sections included, consistent format
You ask: "Model this feature"
β†’ AI jumps straight to code, no planning, creates messy structure
You ask: "Model this feature"
β†’ AI guides you through planning first, asks the right questions, then creates clean structure
Every new session:
You re-explain: "Remember to include X section"
Every new session:
AI already knows β€” standards are loaded automatically
You review AI output:
Manually check if it follows your standards
You review AI output:
AI checks compliance automatically and tells you what's missing
Documentation scattered everywhere:
No clear place for docs, inconsistent structure
Clear documentation structure:
Templates show where everything goes, consistent structure

Workflow Examples

Real Workflows with Actual Prompts

See how context packs work in practice with complete workflow examples.

Workflow 1: Creating Documentation for a New Feature

Step 1: Ask AI to Create Documentation

I'm building a user authentication feature. Create documentation for it following our standards.

What happens: AI automatically uses your pack's templates and structure. It includes all required sections (purpose, how it works, what it does) without you having to remember what sections are needed.

Step 2: AI Checks It Follows Standards

Does this documentation follow our standards?

What happens: AI reviews the documentation against your pack's rules, tells you what's missing or needs fixing, and suggests improvements automatically.

Result: Professional documentation that follows your standards, created in minutes, without you having to remember all the rules.

Workflow 2: Updating Existing Documentation

Step 1: Tell AI What Changed

I updated the authentication feature to add password reset. Update the documentation.

What happens: AI knows which parts of the documentation need updating based on your pack's rules. It updates the right sections and keeps the structure consistent.

Step 2: AI Maintains Consistency

Make sure the updated docs still follow our standards.

What happens: AI ensures the updated documentation still matches your standards, uses the same format, and includes all required information.

Result: Documentation stays up-to-date and consistent, without you having to manually check every section.

Workflow 3: Getting Help When You're Stuck

Step 1: Ask for Guidance

I need to document a new API endpoint. What should I include?

What happens: AI references your pack's templates and tells you exactly what sections you need, what information goes where, and provides examples from your standards.

Step 2: AI Creates It for You

Create the documentation using our template.

What happens: AI creates the documentation following your exact template, filling in the information you provided, ensuring it matches your standards perfectly.

Result: You get help when you need it, and the output always matches your standards β€” no guessing, no inconsistency.

AI is fast β€” but it outputs vary

AI generates outputs that often conflict and vary in their approach β€” even good standards are bad if applied inconsistently. Vibe coders are ignorant of the mess they're creating, and experienced engineers are continually re-explaining rules and guidelines, correcting the same AI mistakes. This isn't limited to AI code generation. Software teams without clear standards and guidelines have been suffering these problems for years β€” long before AI.

Experienced engineers waste time re-teaching

You explain standards, architecture, and preferences. Tomorrow, you explain them again. The cycle repeats because AI has no memory.

Inconsistent output creates technical debt

Different prompts produce different structures. Code quality degrades. Documentation becomes unreliable. You spend more time fixing than building.

Drift happens when standards aren't explicit

AI makes confident changes that violate your conventions. Without explicit guardrails, your codebase drifts further from your standards with each change.

Speed without standards creates chaos

You want AI speed, but you need consistency. Without codified standards, faster output just means faster accumulation of technical debt.

The Solution

Context Packs

Standards, practices, workflows, and more β€” plugged into your codebase. This prevents you and AI from drifting apart, or away from explicit standards.

Teach Cursor and Claude how to get things done with professional knowledge injected into your codebase. Think of it as codified expertise β€” so AI remembers your way of working, not just for one session, but permanently.

Standards live in your codebase

Version-controlled, reviewable, and evolvable. Your standards are code, not documentation that gets ignored.

Modular knowledge injection

Add packs incrementally. Each pack solves one problem with concrete structure, templates, and workflows.

Consistent output, every time

AI reads your standards automatically. No re-explaining. No drift. Predictable, maintainable output.

Built for how AI tools work

Designed for Cursor/Claude's context consumption. Not a workaround β€” a proper solution that fits how these tools actually operate.

Available Packs

Packs for specific problems.

Each pack codifies one specific area of expertise with concrete structure, templates, and workflows.

Pack 01 β€” Documentation Management

When AI generates documentation, do you struggle with where it goes or how to keep it organized? Pack 01 gives Cursor/Claude a repeatable documentation structure - so docs don't rot or drift over time.

Available now
DocsStructureCursorClaude
View pack

Pack 02 β€” PR Quality & AI Output Review

Stop risky AI changes from slipping into main. Standardize review workflows, checklists, and β€œdiff-first” prompts so PRs stay safe and predictable.

Coming soon
ReviewQualitySafety
Coming soon

Pack 03 β€” Codebase Structure & Boundaries

Prevent repo spaghetti. Give AI clear rules for where new code goes, how modules are organized, and what boundaries must not be crossed.

Coming soon
StructureBoundariesMaintainability
Coming soon

Pack 04 β€” Architecture Decisions (ADR Guardrails)

Keep architecture consistent and explainable. Make AI propose tradeoffs, record decisions as ADRs, and update them as the system evolves.

Coming soon
ArchitectureADRsConsistency
Coming soon

Pack 05 β€” Code Standards (Naming, Time, Lifecycle)

Eliminate style drift and subtle bugs. Standardize naming, timezone/time handling, lifecycle fields, and β€œhow we write code here” conventions.

Coming soon
StandardsCorrectnessConsistency
Coming soon

Pack 06 β€” Database Change Safety (Migrations & Repos)

Make schema changes safer. Give AI guardrails for migrations, transactional boundaries, repository/session patterns, and rollback-friendly updates.

Coming soon
DatabaseMigrationsSafety
Coming soon

Pack 07 β€” API Design Guardrails (REST & Integrations)

Stop inconsistent endpoints. Standardize resources, errors, pagination, versioning, and integration patterns so APIs stay coherent as you scale.

Coming soon
APIRESTConsistency
Coming soon

Pack 08 β€” Frontend Data Architecture (React Query)

Avoid fragile frontend state. Establish rules for server-state vs client-state, React Query patterns, and feature organization that AI must follow.

Coming soon
FrontendReact QueryStructure
Coming soon

Bundle β€” Ship to Production (IaC + CI/CD Editions)

Deploy without guessing. Tool-specific editions that provide infrastructure baseline + CI/CD pipeline patterns for repeatable production releases.

Coming soon
IaCCI/CDDeployment
Coming soon
Get Pack 01

Not sure yet? Share feedback β€” it helps shape the next packs.

Installation Guide

Detailed installation steps

Follow these steps to install your first context pack and start using it with Cursor or Claude.

1

Install the CLI tool

Install the Context CLI tool (one-time setup):

# Using npm:
npm install -g @zebralabs/context-cli

This installs the `ctx` command globally on your machine.

2

Purchase and get your token

After purchasing a context pack, you'll receive:

  • A download link for the pack ZIP file
  • An authentication token (sent via email)

Keep your token safe β€” you'll need it to download packs.

3

Install the pack in your repository

Open your terminal in your project directory and run:

ctx pack install pack-01-documentation-management \
--registry https://www.zebralabs.io/api \
--token YOUR_TOKEN_HERE

Replace YOUR_TOKEN_HERE with the token from your email.

4

Verify installation

Check that the pack was installed correctly:

ctx list

You should see "pack-01-documentation-management" listed. The pack files are now in yourpractices-and-standards/ folder.

5

Start using with Cursor or Claude

That's it! The context pack is now part of your repository. When you use Cursor or Claude:

  • AI automatically reads the pack's standards and templates
  • Generated code and documentation follow your standards
  • No need to re-explain your preferences every session

Try asking Cursor: "Generate a component specification following our documentation standards"

Need Help?

Each pack includes detailed installation instructions and a Quick Start guide. If you run into any issues, contact us β€” we're here to help.

Tell us about your project

We're all ears.