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Contributor Covenant Code of Conduct

Our Pledge

We as contributors and maintainers pledge to make participation in this project a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.

Our Standards

Examples of behavior that contributes to a positive environment:

  • Using welcoming and inclusive language
  • Being respectful of differing viewpoints and experiences
  • Gracefully accepting constructive criticism
  • Focusing on what is best for the community

Examples of unacceptable behavior:

  • Trolling, insulting or derogatory comments, and personal or political attacks
  • Public or private harassment
  • Publishing others' private information without explicit permission
  • Other conduct which could reasonably be considered inappropriate in a professional setting

Enforcement

Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by opening an issue or contacting the maintainer directly. All complaints will be reviewed and investigated promptly.

Attribution

This Code of Conduct is adapted from the Contributor Covenant, version 2.1.

  1. Commit with message: meta: add code of conduct

Step 5: Set up your profile README

  1. Go to https://github.com/new
  2. Create a repo named exactly asakin (same as your username). Must be public. Check "Add a README file."
  3. Open the README and replace everything with this:

markdown

Ariel Sakin

Software engineer, operations person, occasional CIO. I spend most of my time making systems work: infrastructure, processes, and increasingly, AI tooling.

Currently building: llm-context-base - an opinionated git template for building personal knowledge bases with LLMs. Based on Karpathy's LLM Wiki pattern, extended with a training period, metadata standard, and health checks.

Background: Engineering and operations, with a lean toward systems that compound over time rather than ones that require constant maintenance.

Interests: AI/ML tooling, personal knowledge systems, home automation, making things that actually work and then leaving them alone.

llm-context-base · Apache 2.0 · use the template