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Add skills

Upload custom SKILL.md files to give your managed agent domain-specific instructions.

Skills are instruction files that teach your managed agent how to handle specific tasks. When the system prompt is not detailed enough for a multi-step workflow or a domain-specific process, a skill fills the gap.

What a skill looks like

A skill is a SKILL.md file written in Markdown. It contains step-by-step instructions the AI platform follows when a relevant situation comes up in a conversation.

A skill might describe:

  • How to triage a support ticket and assign it to the right team.
  • How to walk a user through an onboarding checklist.
  • How to pull data from an MCP server and format it as a summary.

The AI platform reads the skill and applies the instructions when it decides the skill is relevant to the current conversation turn.

Add a skill from GitHub

  1. Open the Novu dashboard and go to your managed agent's detail page.
  2. Open the Skills section in the agent settings.
  3. Select GitHub URL as the source.
  4. Paste the public repository URL. You can point to:
    • The root of a repo (Novu looks for SKILL.md at the top level).
    • A specific branch or subfolder (e.g. https://github.com/org/repo/tree/main/skills/triage).
  5. Click Upload.

Novu downloads the files, bundles them, and sends them to the AI platform. The platform assigns a stable skill ID.

Add a skill inline

  1. Open the Skills section in the agent settings.
  2. Select Inline content as the source.
  3. Paste your SKILL.md content directly into the text field.
  4. Click Upload.

This is useful for quick iterations or skills that do not need to live in a repository.

Versioning

If you upload a skill with the same display title as an existing one, the platform creates a new version automatically. The agent always uses the latest version.

Remove a skill

To remove a skill, go to the Skills section and delete it from the list. The agent stops using the skill on the next conversation turn.

Tips for writing good skills

  • Be specific: describe the exact steps the agent should follow, not just the goal.
  • Include examples: show sample inputs and expected outputs when possible.
  • Keep it focused: one skill per task. A skill that tries to cover too many scenarios becomes harder for the model to apply correctly.
  • Test with real conversations: send messages that should trigger the skill and check whether the agent follows the instructions.

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