AGF

Contribute

How to contribute to AGF — challenges, evidence, corrections, and pattern proposals all welcome.

AGF is built on community over credit — if this framework helps one organization build a safer agentic system, it has served its purpose. We welcome challenges to claims, evidence from real-world implementations, proposals for new patterns, and corrections to what we got wrong.

The canonical CONTRIBUTING.md on GitHub is the source of truth. This page summarizes the highest-leverage contribution paths.

Where to start

If you want to...Go to
Ask a question or discuss an experienceGitHub Discussions
Report a factual error or broken referenceGitHub Issues
Propose a content changePull request against docs/*.md (canonical source)
Challenge a claim or framework decisionDiscussion under "Challenge & Critique"
Propose a change to intent.mdDiscussion only — intent.md is sacred

What we welcome

  • Challenge & Critique. Where is AGF wrong? What are we overclaiming? What did we miss?
  • Evidence & Implementation. Real-world experiences implementing the patterns. What worked, what didn't, what surprised you.
  • Standards updates. When AICM, NIST AI RMF, ISO 42001, EU AI Act, or similar issues a new revision, mappings need refresh.
  • Pattern proposals. New primitives or composition patterns — accompanied by the problem they solve and the evidence supporting them.
  • Diagram improvements. Architecture diagrams are first-class artifacts.

Content conventions

Canonical source

Edit docs/*.md files (the canonical source). The site MDX files (agf-docs/content/docs/*.mdx) are derived. If you submit a PR against an .mdx file, it will be redirected to the canonical source.

Voice

  • Humility before authority. AGF synthesizes; it does not decree. Credit the work AGF builds on.
  • Rigor before opinion. Every claim either traces to a cited source OR carries an explicit <Confidence level /> label.
  • No undefended novelty. Where AGF introduces a new framing, it is marked <Confidence level="informed" /> until adopter evidence promotes it to established, or counter-evidence demotes it to open.

Confidence levels

Use one of three labels on any new claim:

  • <Confidence level="established" /> — proven across multiple domains; multiple sources would agree.
  • <Confidence level="informed" /> — AGF's synthesis; plausible but unverified at scale.
  • <Confidence level="open" /> — flagged but speculative; needs investigation.

See Confidence Levels for the full rationale.

Standards references

When citing existing work:

  • Include specific document names, version numbers, and dates (not just organization names).
  • Explain how the reference relates to AGF (not just that it exists).
  • Prefer primary sources over summaries.

Cross-reference integrity

Framework documents reference each other by primitive number (#1–#19). If your change affects primitive numbering or naming, note which downstream documents need updates.

Review process

All contributions are reviewed by the maintainer. For framework content, the four review dimensions are:

  1. Accuracy — Is the claim correct? Is the standards mapping accurate?
  2. Voice — Does it maintain AGF's synthesis positioning?
  3. Confidence — Are new claims appropriately marked?
  4. Cross-references — Does it maintain integrity with adjacent docs?

External reviews land in docs/reviews/; tracked findings land in docs/findings-ledger.md with stable F-IDs that survive across revisions.

Code of conduct

AGF deals with governance and safety; the community that builds it should reflect those values.

  • Critique the ideas, not the people.
  • Back claims with evidence or clearly mark them as proposals.
  • Acknowledge what you don't know.

License

By contributing, you agree your contributions are licensed under the same terms as the project — CC BY 4.0 for documentation; Apache-2.0 / MIT for any code or tooling. See LICENSE for details.


The most valuable contributions are usually evidence from a real implementation — even partial, even with caveats. AGF's biggest gap today is the absence of adopter case studies; if you've built on it, your experience is exactly what would close that gap.

On this page