AI Agent

GitHub release notes agent

Automatically turn commits, pull requests, and diffs into polished release notes that communicate benefits and user value.

View code
CONTACT US
Loved by engineers at
Tab 1
Tab 2
Tab 1
Tab 2
Tab 3
Tab 1
Tab 1
Tab 2
Tab 1
Tab 2
Tab 1
Tab 2

Release communication, done right

This agentic workflow transforms raw release documentation into clear, benefit-focused copy that resonates with leaders and decision-makers, helping you capture the most marketing impact from engineering.

GitHub-native change analysis

The GitHub agent connects directly to GitHub and analyzes commits, pull requests, and code changes to understand exactly what shipped.

Automatically filter updates

Built-in decision frameworks determine which changes are fit-for-marketing, while automatically filtering out internal refactors, dependency bumps, test changes, and CI/CD tweaks.

Clear, customer-facing release notes

The agentic workflow converts technical changes into benefit-driven language that product leaders, customers, and stakeholders can immediately understand.

Update at release speed

The agentic workflow can be triggered on every release, tag, or milestone—eliminating manual writing cycles, reducing engineering overhead, and keeping changelogs continuously up to date.

From commit history to publish-ready notes in one run

Point the agent at a release, tag, or milestone, and it handles the rest by pulling the changes, deciding what matters for users, and writing the entry in your voice.

  1. Connect your repo
    Authenticate with GitHub and select the repository, branch, or release you want to document.
  1. Run the workflow
    The agent pulls commits, pull requests, and diffs for the selected range and analyzes what actually shipped.
  1. Review and publish
    Get a structured draft with user-facing changes grouped by theme, internal noise filtered out, and language tuned for your audience, ready to copy into your changelog, blog, or product email.

Agno’s GitHub release notes agentic workflow uses three specialized agents working in sequence

Each agent is purpose-built for its role, ensuring consistent, high-quality output every time.

The Extractor

Analyzes your GitHub release, comparing commits, pull requests, and file changes to extract structured facts about what changed

‍

The Categorizer

Applies a rigorous 4-question framework to determine which changes matter to your users vs. which are internal housekeeping

‍

The Author

Transforms technical changes into clear, benefit-focused entries that resonate with engineering leaders and decision-makers

Quickly deploy production agents_

Agno delivers best-practice infrastructure that you don't have to build, maintain, or migrate off of as the field moves.

Production-ready out of the box

Sessions, streaming, memory, knowledge, traces, JWT auth, RBAC. 50+ OpenAPI-spec'd endpoints. No glue code to your frontend.

Still works in six months

MCP, new models, new tool-calling patterns land in days, not quarters. The agent you ship today doesn't go stale when the field moves.

Complete data privacy

Privacy and security are built into the architecture. Your data never leaves your system.

While you’re here, check out these other pre-built AI agents_

Self-learning Data Agent

Self-learning data agent built for enterprise. Customizable to your data, business logic, and workflows.
View Agent