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Why Standards Matter with AI Agents

Standards are one of three artifact types in Packmind, alongside commands and skills. Context engineering is key to making the most of AI coding assistants. Standards are guidelines that drive the output of agents, ensuring they generate code that follows your team’s conventions and best practices. Many teams struggle with documentation that nobody reads or maintains—wikis and Markdown files that become outdated quickly. With AI coding assistants, this problem becomes even more critical. Standards make your written documentation useful again by providing consistent, actionable guidance that AI agents can follow automatically.

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Understand Standards and Rules

A standard is an agreed-upon, documented set of rules or criteria that ensures consistent, compatible, and high-quality code across your team. Here is a basic example of a standard:
Standard: Back-end unit testsRules for this standard:
  • Use assertive names in test names (it("returns ..." instead of it("should return"))
  • Structure tests with the AAA pattern
  • Single expect per test

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Create Standards with AI Agents

You can create standards using the /packmind-update-playbook skill in your AI coding assistant. Simply type: 
/packmind-update-playbook create a Packmind standard about unit tests with Jest
Or use a natural language prompt like: “Create a Packmind standard ‘Unit tests with Jest’ and extract coding rules by analyzing the file @test.spec.ts” The AI agent will automatically follow a guided workflow to ensure high-quality standards:
  1. Gather context from your codebase and iterate with you on the draft
  2. Create the standard with rules and code examples
For more details, see the Create Your First Standard guide.

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Create Standards Through UI

Go to the Standards menu and create your first standard. The description area supports Markdown so you can give more context about it. Add your first rules, ideally with one clear detailed sentence. The scope let you define files and folders patterns where the standard applies. For instance, you may want to use **/*.spec.ts if your standard is related to tests. You can update your standard later to add and remove rules. Each rule can be documented with code examples as well.

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Standards Versions

Every time you update a standard, this creates a new version. This keeps track of the history of your changes, and it’s useful to keep track of which versions are currently distributed to Git repositories. You can submit local changes to your standards using: 
packmind-cli playbook add <path/to/standard.md>
packmind-cli playbook submit
Use --no-review to trigger a direct update. Omit --no-review to use the change proposals system and get validation of your changes.

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Where Standards Appear After Distribution

Once you distribute a package containing standards, they appear in specific locations in your repository depending on which AI assistants your organization has enabled. Standards are automatically loaded by your AI assistant—you don’t need to do anything special to activate them. For detailed information about where standards appear for each AI assistant, see Understanding Where Your Artifacts Appear.