kubernetes / kubernetes/community

Improve New Contributor Onboarding via Emoji-Triggered Resource Hub + Weekly Starter Post

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#8,935 4 comments 1 reaction 0 assignees View on GitHub
sig/contributor-experience
Dominant language
Jupyter Notebook
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Description

### Describe the issue

**Problem**

In the [#kubernetes-new-contributors](https://kubernetes.slack.com/archives/C09R23FHP) Slack channel, new contributors often introduce themselves but are unsure how to proceed. This leads to:

- Repetitive onboarding guidance from maintainers
- Low follow-up engagement from new contributors
- Difficulty navigating the broader ecosystem (Kubernetes core, SIGs, and related repos)

**Proposal**

Introduce a lightweight onboarding improvement using:

1. Emoji-triggered Slack workflow
When a new contributor posts an introduction, a maintainer (or community member) reacts with a specific emoji (e.g., 👋)
This triggers a Slack Workflow response sharing a centralized, interactive resource hub:
Such as https://irapandey.github.io/k8s-resource/ - this is a complication of lists I found floating in the channel by maintainers.

2. Weekly automated starter post
A recurring message in the channel

- Directs users to the resource hub
- Encourages them to pick a starting path
- Nudges engagement with:
- “Made your first contribution this week? Share it here!”

**Why this helps**

- Reduces repetitive onboarding responses
- Provides a clear and structured starting point
- Improves discoverability across SIGs and contribution areas
- Encourages organic interaction and community participation

Contributor guide

Open the contributing guide

Research direction

Start in the #kubernetes-new-contributors Slack channel and review the linked resource hub at https://irapandey.github.io/k8s-resource/. Clarify the emoji-triggered workflow and recurring starter post requirements with the community maintainers. Done means both onboarding mechanisms are defined, configured, and provide the proposed resource and engagement prompts.

Written by the indexing model from the issue text.

Assessment

Domain
developer-experience, documentation
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
45/100

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